- b - Variable in class ec.eda.CMAESSpecies
-
The "B" matrix, eigendecomposed from the "C" covariance matrix of the distribution.
- backupPopulation - Variable in class ec.simple.SimpleBreeder
-
- BAD_TREE - Static variable in class ec.gp.ge.GEIndividual
-
- BadParameterException - Exception in ec.util
-
Thrown when you attempt to create a Parameter from bad path items.
- BadParameterException(String) - Constructor for exception ec.util.BadParameterException
-
- BarChartStatistics - Class in ec.display.chart
-
- BarChartStatistics() - Constructor for class ec.display.chart.BarChartStatistics
-
- base() - Static method in class ec.breed.BreedDefaults
-
Returns the default base.
- base() - Static method in class ec.ECDefaults
-
Returns the default base.
- base() - Static method in class ec.eda.EDADefaults
-
Returns the default base.
- base() - Static method in class ec.es.ESDefaults
-
Returns the default base.
- base - Variable in class ec.eval.MetaProblem
-
The parameter base from which the MetaProblem was loaded.
- base - Variable in class ec.exchange.InterPopulationExchange
-
My parameter base -- I need to keep this in order to help the server
reinitialize contacts
- base - Variable in class ec.exchange.IslandExchange
-
My parameter base -- I need to keep this in order to help the server
reinitialize contacts
- base() - Static method in class ec.gp.breed.GPBreedDefaults
-
Returns the default base, which is built off of the GPDefaults base.
- base() - Static method in class ec.gp.build.GPBuildDefaults
-
Returns the default base.
- base() - Static method in class ec.gp.ge.GEDefaults
-
Returns the default base.
- base() - Static method in class ec.gp.GPDefaults
-
Returns the default base.
- base() - Static method in class ec.gp.koza.GPKozaDefaults
-
Returns the default base, which is built off of the GPDefaults base.
- base() - Static method in class ec.gp.push.PushDefaults
-
Returns the default base.
- base() - Static method in class ec.multiobjective.MultiObjectiveDefaults
-
Returns the default base.
- base() - Static method in class ec.rule.RuleDefaults
-
Returns the default base.
- base() - Static method in class ec.select.SelectDefaults
-
Returns the default base.
- base() - Static method in class ec.simple.SimpleDefaults
-
Returns the default base.
- base() - Static method in class ec.spatial.SpatialDefaults
-
Returns the default base.
- base() - Static method in class ec.steadystate.SteadyStateDefaults
-
Returns the default base.
- base() - Static method in class ec.vector.VectorDefaults
-
Returns the default base.
- batchMode - Variable in class ec.eval.MasterProblem
-
- bd - Variable in class ec.eda.CMAESSpecies
-
b x d
- beforeCoevolutionaryEvaluation(EvolutionState, Population, GroupedProblemForm) - Method in class ec.coevolve.MultiPopCoevolutionaryEvaluator
-
- Best1BinDEBreeder - Class in ec.de
-
Best1BinDEBreeder is a differential evolution breeding operator.
- Best1BinDEBreeder() - Constructor for class ec.de.Best1BinDEBreeder
-
- best_of_run - Variable in class ec.simple.SimpleStatistics
-
The best individual we've found so far
- bestn - Variable in class ec.select.BestSelection
-
- bestnFrac - Variable in class ec.select.BestSelection
-
- bestOfGeneration - Variable in class ec.simple.SimpleShortStatistics
-
- BestSelection - Class in ec.select
-
Performs a tournament selection restricted to only the best, or worst, n
indivdiuals in the population.
- BestSelection() - Constructor for class ec.select.BestSelection
-
- bestSoFar - Variable in class ec.simple.SimpleShortStatistics
-
- bestSoFarIndex - Variable in class ec.de.DEBreeder
-
the best individuals in each population (required by some DE breeders).
- bestUnderlyingIndividual - Variable in class ec.eval.MetaProblem
-
The best underlying individual array, one per subpopulation.
- betterThan(Fitness) - Method in class ec.Fitness
-
Should return true if this fitness is clearly better than _fitness;
You may assume that _fitness is of the same class as yourself.
- betterThan(Fitness) - Method in class ec.gp.koza.KozaFitness
-
- betterThan(Fitness) - Method in class ec.multiobjective.MultiObjectiveFitness
-
Returns true if I'm better than _fitness.
- betterThan(Fitness) - Method in class ec.multiobjective.nsga2.NSGA2MultiObjectiveFitness
-
We specify the tournament selection criteria, Rank (lower
values are better) and Sparsity (higher values are better)
- betterThan(Fitness) - Method in class ec.multiobjective.spea2.SPEA2MultiObjectiveFitness
-
The selection criteria in SPEA2 uses the computed fitness, and not
pareto dominance.
- betterThan(Individual, Individual, int, EvolutionState, int) - Method in class ec.parsimony.LexicographicTournamentSelection
-
- betterThan(Individual, Individual, int, EvolutionState, int) - Method in class ec.parsimony.ProportionalTournamentSelection
-
- betterThan(Individual, Individual, int, EvolutionState, int) - Method in class ec.select.TournamentSelection
-
Returns true if *first* is a better (fitter, whatever) individual than *second*.
- betterThan(Fitness) - Method in class ec.simple.SimpleFitness
-
- BIG_TREE_ERROR - Static variable in class ec.gp.ge.GESpecies
-
- BitVectorIndividual - Class in ec.vector
-
BitVectorIndividual is a VectorIndividual whose genome is an array of booleans.
- BitVectorIndividual() - Constructor for class ec.vector.BitVectorIndividual
-
- BitVectorSpecies - Class in ec.vector
-
BitVectorSpecies is a subclass of VectorSpecies with special
constraints for boolean vectors, namely BitVectorIndividual.
- BitVectorSpecies() - Constructor for class ec.vector.BitVectorSpecies
-
- BoltzmannSelection - Class in ec.select
-
Similar to FitProportionateSelection, but with a Simulated Annealing style twist.
- BoltzmannSelection() - Constructor for class ec.select.BoltzmannSelection
-
- BOOLEAN_CONSTANT - Static variable in class ec.gp.ge.GrammarParser
-
- BreedDefaults - Class in ec.breed
-
- BreedDefaults() - Constructor for class ec.breed.BreedDefaults
-
- Breeder - Class in ec
-
A Breeder is a singleton object which is responsible for the breeding
process during the course of an evolutionary run.
- Breeder() - Constructor for class ec.Breeder
-
- breeder - Variable in class ec.EvolutionState
-
The population breeder, a singleton object.
- breedIndividual(EvolutionState, int, int) - Method in class ec.steadystate.SteadyStateBreeder
-
- BreedingPipeline - Class in ec
-
A BreedingPipeline is a BreedingSource which provides "fresh" individuals which
can be used to fill a new population.
- BreedingPipeline() - Constructor for class ec.BreedingPipeline
-
- BreedingSource - Class in ec
-
A BreedingSource is a Prototype which
provides Individuals to populate new populations based on
old ones.
- BreedingSource() - Constructor for class ec.BreedingSource
-
- breedPopChunk(Population, EvolutionState, int[], int[], int) - Method in class ec.es.MuCommaLambdaBreeder
-
A private helper function for breedPopulation which breeds a chunk
of individuals in a subpopulation for a given thread.
- breedPopChunk(Population, EvolutionState, int[], int[], int) - Method in class ec.simple.SimpleBreeder
-
A private helper function for breedPopulation which breeds a chunk
of individuals in a subpopulation for a given thread.
- breedPopChunk(Population, EvolutionState, int[], int[], int) - Method in class ec.spatial.SpatialBreeder
-
- breedPopulation(EvolutionState) - Method in class ec.Breeder
-
Breeds state.population, returning a new population.
- breedPopulation(EvolutionState) - Method in class ec.de.DEBreeder
-
- breedPopulation(EvolutionState) - Method in class ec.eda.CMAESBreeder
-
Updates the CMA-ES distribution given the current population, then
replaces the population with new samples generated from the distribution.
- breedPopulation(EvolutionState) - Method in class ec.es.MuCommaLambdaBreeder
-
- breedPopulation(EvolutionState) - Method in class ec.multiobjective.nsga2.NSGA2Breeder
-
Override breedPopulation().
- breedPopulation(EvolutionState) - Method in class ec.pso.PSOBreeder
-
- breedPopulation(EvolutionState) - Method in class ec.simple.SimpleBreeder
-
A simple breeder that doesn't attempt to do any cross-
population breeding.
- breedthreads - Variable in class ec.EvolutionState
-
The requested number of threads to be used in breeding, excepting perhaps a "parent" thread which gathers the other threads.
- BucketTournamentSelection - Class in ec.parsimony
-
Does a tournament selection, limited to the subpopulation it's
working in at the time.
- BucketTournamentSelection() - Constructor for class ec.parsimony.BucketTournamentSelection
-
- buffer - Variable in class ec.breed.BufferedBreedingPipeline
-
- BufferedBreedingPipeline - Class in ec.breed
-
If empty, a
BufferedBreedingPipeline makes a request of exactly num-inds
individuals from a single child source; it then uses these
individuals to fill requests (returning min each time),
until the buffer is emptied, at
which time it grabs exactly num-inds more individuals, and so on.
- BufferedBreedingPipeline() - Constructor for class ec.breed.BufferedBreedingPipeline
-
- buildArchive(EvolutionState, int) - Method in class ec.multiobjective.nsga2.NSGA2Evaluator
-
Build the auxiliary fitness data and reduce the subpopulation to just the archive, which is
returned.
- buildArchive(EvolutionState, Individual[], Individual[], int) - Method in class ec.multiobjective.spea2.SPEA2Breeder
-
- buildDyckWord(int, int[], int[], EvolutionState, int) - Method in class ec.gp.build.RandTree
-
- builder - Variable in class ec.gp.koza.MutationPipeline
-
How the pipeline builds a new subtree
- buildOutput() - Static method in class ec.Evolve
-
Constructs and sets up an Output object.
- buildTree(EvolutionState, int) - Method in class ec.gp.GPTree
-
Builds a new randomly-generated rooted tree and attaches it to the GPTree.
- buildTreeModel() - Method in class ec.util.ParameterDatabase
-
Builds a TreeModel from the available property keys.
- bypassFinalStatistics(EvolutionState, int) - Method in class ec.simple.SimpleStatistics
-
Allows MultiObjectiveStatistics etc.
- ByteVectorIndividual - Class in ec.vector
-
ByteVectorIndividual is a VectorIndividual whose genome is an array of bytes.
- ByteVectorIndividual() - Constructor for class ec.vector.ByteVectorIndividual
-
- c - Variable in class ec.eda.CMAESSpecies
-
The "C" covariance matrix of the distribution.
- c1 - Variable in class ec.eda.CMAESSpecies
-
The c_1 rank-1 update learning rate.
- C_ANY_POINT - Static variable in class ec.vector.VectorSpecies
-
- C_AUTO - Static variable in class ec.simple.SimpleEvaluator
-
- C_CLASS - Static variable in class ec.util.ParameterDatabase
-
- C_EXACTLY_ONE_FIFTH_BETTER - Static variable in class ec.es.MuCommaLambdaBreeder
-
- C_FLIP_MUTATION - Static variable in class ec.vector.BitVectorSpecies
-
- C_GAUSS_MUTATION - Static variable in class ec.vector.FloatVectorSpecies
-
- C_GEOMETRIC - Static variable in class ec.vector.VectorSpecies
-
- C_HERE - Static variable in class ec.util.ParameterDatabase
-
- C_INTEGER_RANDOM_WALK_MUTATION - Static variable in class ec.vector.FloatVectorSpecies
-
- C_INTEGER_RESET_MUTATION - Static variable in class ec.vector.FloatVectorSpecies
-
- C_INTERMED_RECOMB - Static variable in class ec.vector.VectorSpecies
-
- C_LINE_RECOMB - Static variable in class ec.vector.VectorSpecies
-
- C_NEIGHBORHOOD_RANDOM - Static variable in class ec.pso.PSOBreeder
-
- C_NEIGHBORHOOD_RANDOM_EACH_TIME - Static variable in class ec.pso.PSOBreeder
-
- C_NEIGHBORHOOD_TOROIDAL - Static variable in class ec.pso.PSOBreeder
-
- C_NONE - Static variable in class ec.vector.VectorSpecies
-
- C_ONE_POINT - Static variable in class ec.vector.VectorSpecies
-
- C_ONE_POINT_NO_NOP - Static variable in class ec.vector.VectorSpecies
-
- C_OVER_ONE_FIFTH_BETTER - Static variable in class ec.es.MuCommaLambdaBreeder
-
- C_POLYNOMIAL_MUTATION - Static variable in class ec.vector.FloatVectorSpecies
-
- C_RANDOM_WALK_MUTATION - Static variable in class ec.vector.IntegerVectorSpecies
-
- C_RESET_MUTATION - Static variable in class ec.vector.BitVectorSpecies
-
- C_RESET_MUTATION - Static variable in class ec.vector.FloatVectorSpecies
-
- C_RESET_MUTATION - Static variable in class ec.vector.IntegerVectorSpecies
-
- C_SIMULATED_BINARY - Static variable in class ec.vector.VectorSpecies
-
- C_STARTED_FRESH - Static variable in class ec.EvolutionState
-
"The population has started fresh (not from a checkpoint)."
- C_STARTED_FROM_CHECKPOINT - Static variable in class ec.EvolutionState
-
"The population started from a checkpoint."
- C_TWO_POINT - Static variable in class ec.vector.VectorSpecies
-
- C_TWO_POINT_NO_NOP - Static variable in class ec.vector.VectorSpecies
-
- C_UNDER_ONE_FIFTH_BETTER - Static variable in class ec.es.MuCommaLambdaBreeder
-
- C_UNIFORM - Static variable in class ec.vector.VectorSpecies
-
- CACHE_SIZE - Static variable in class ec.gp.build.PTCFunctionSet
-
- calculateDistances(EvolutionState, Individual[]) - Method in class ec.multiobjective.spea2.SPEA2Evaluator
-
Returns a matrix of sum squared distances from each individual to each other individual.
- calculateDistancesFromIndividual(Individual, Individual[]) - Method in class ec.multiobjective.spea2.SPEA2Breeder
-
- canEvaluate() - Method in class ec.eval.MasterProblem
-
- canEvaluate() - Method in class ec.gp.ge.GEProblem
-
- canEvaluate() - Method in class ec.Problem
-
Asynchronous Steady-State EC only: Returns true if the problem is ready to evaluate.
- canEvaluate() - Method in class ec.steadystate.SteadyStateEvaluator
-
Returns true if we're ready to evaluate an individual.
- canPick() - Method in class ec.gp.GPNodeBuilder
-
Returns true if some size distribution (either minSize and maxSize,
or sizeDistribution) is set up by the user in order to pick sizes randomly.
- cc - Variable in class ec.eda.CMAESSpecies
-
The c_c rank-one evolution path cumulation parameter.
- ChartableStatistics - Class in ec.display.chart
-
- ChartableStatistics() - Constructor for class ec.display.chart.ChartableStatistics
-
- chatty - Variable in class ec.exchange.InterPopulationExchange
-
- CHECK_BOUNDARY - Static variable in class ec.gp.GPNodeBuilder
-
- CHECKBOUNDARY - Static variable in class ec.util.RandomChoice
-
- checkConstraints(EvolutionState, int, GPIndividual, Parameter) - Method in class ec.gp.ADF
-
Checks type-compatibility constraints between the ADF, its argument terminals, and the tree type of its associated tree, and also checks to make sure the tree exists, there aren't invalid argument terminals in it, and there are sufficient argument terminals (a warning).
- checkConstraints(EvolutionState, int, GPIndividual, Parameter) - Method in class ec.gp.GPNode
-
You ought to override this method to check to make sure that the
constraints are valid as best you can tell.
- checkDyckWord(String) - Method in class ec.gp.build.RandTree
-
- checkForHelp(String[]) - Static method in class ec.Evolve
-
Optionally prints the help message.
- CheckingPipeline - Class in ec.breed
-
CheckingPipeline is a BreedingPipeline which just passes through the
individuals it receives from its source 0, but only if those individuals
ALL pass a validation check (the method allValid(), which you must override).
- CheckingPipeline() - Constructor for class ec.breed.CheckingPipeline
-
- checkpoint - Variable in class ec.EvolutionState
-
Should we checkpoint at all?
- Checkpoint - Class in ec.util
-
Checkpoints ec.EvolutionState objects out to checkpoint files, or
restores the same from checkpoint files.
- Checkpoint() - Constructor for class ec.util.Checkpoint
-
- checkpointDirectory - Variable in class ec.EvolutionState
-
The requested directory where checkpoints should be located.
- checkpointModulo - Variable in class ec.EvolutionState
-
The requested number of generations that should pass before we write out a checkpoint file.
- checkpointPrefix - Variable in class ec.EvolutionState
-
The requested prefix to start checkpoint filenames, not including a following period.
- checkPreamble(String, EvolutionState, LineNumberReader) - Static method in class ec.util.Code
-
Finds the next nonblank line, then trims the line and checks the preamble.
- child - Variable in class ec.gp.GPTree
-
the root GPNode in the GPTree
- CHILD_D - Variable in class ec.gp.build.Uniform
-
- children - Variable in class ec.gp.ge.GrammarNode
-
- children - Variable in class ec.gp.GPNode
-
- children - Variable in class ec.Statistics
-
- CHILDREN_UNKNOWN - Static variable in class ec.gp.GPNode
-
- childtypes - Variable in class ec.gp.GPNodeConstraints
-
The children types for a GPNode
- chiN - Variable in class ec.eda.CMAESSpecies
-
An estimate of the expected size of the standard multivariate gaussian N(0,I).
- chunksize - Variable in class ec.vector.VectorSpecies
-
How big of chunks should we define for crossover?
- clamp() - Method in class ec.vector.ByteVectorIndividual
-
Clips each gene value to be within its specified [min,max] range.
- clamp() - Method in class ec.vector.DoubleVectorIndividual
-
Clips each gene value to be within its specified [min,max] range.
- clamp() - Method in class ec.vector.FloatVectorIndividual
-
Clips each gene value to be within its specified [min,max] range.
- clamp() - Method in class ec.vector.IntegerVectorIndividual
-
Clips each gene value to be within its specified [min,max] range.
- clamp() - Method in class ec.vector.LongVectorIndividual
-
Clips each gene value to be within its specified [min,max] range.
- clamp() - Method in class ec.vector.ShortVectorIndividual
-
Clips each gene value to be within its specified [min,max] range.
- cleanup(EvolutionState) - Static method in class ec.Evolve
-
Begins a fresh evolutionary run with a given state.
- clear() - Method in class ec.Population
-
Sets all Individuals in the Population to null, preparing it to be reused.
- clear() - Method in class ec.Subpopulation
-
Sets all Individuals in the Subpopulation to null, preparing it to be reused.
- clearAnnouncements() - Method in class ec.util.Output
-
Clears out announcements.
- clearErrors() - Method in class ec.util.Output
-
Clears the error flag.
- clearGaussian() - Method in class ec.util.MersenneTwister
-
Clears the internal gaussian variable from the RNG.
- clearGaussian() - Method in class ec.util.MersenneTwisterFast
-
Clears the internal gaussian variable from the RNG.
- clientPort - Variable in class ec.exchange.IslandExchange
-
The port of the client mailbox
- Clique - Interface in ec
-
Clique is a class pattern marking classes which
create only a few instances, generally accessible through
some global mechanism, and every single
one of which gets its own distinct setup(...) call.
- clone() - Method in class ec.breed.UniquePipeline
-
- clone() - Method in class ec.BreedingPipeline
-
- clone() - Method in class ec.BreedingSource
-
- clone() - Method in class ec.eda.CMAESSpecies
-
- clone() - Method in class ec.eval.MasterProblem
-
- clone() - Method in class ec.Fitness
-
- clone() - Method in class ec.gp.ADFContext
-
- clone() - Method in class ec.gp.ADFStack
-
- clone() - Method in class ec.gp.breed.InternalCrossoverPipeline
-
- clone() - Method in class ec.gp.breed.MutateAllNodesPipeline
-
- clone() - Method in class ec.gp.breed.MutateERCPipeline
-
- clone() - Method in class ec.gp.breed.MutateOneNodePipeline
-
- clone() - Method in class ec.gp.breed.SizeFairCrossoverPipeline
-
- clone() - Method in class ec.gp.ge.GEProblem
-
- clone() - Method in class ec.gp.ge.GESpecies
-
- clone() - Method in class ec.gp.ge.GrammarParser
-
- clone() - Method in class ec.gp.GPData
-
- clone() - Method in class ec.gp.GPIndividual
-
Deep-clones the GPIndividual.
- clone() - Method in class ec.gp.GPNode
-
Deep-clones the tree rooted at this node, and returns the entire
copied tree.
- clone() - Method in class ec.gp.GPNodeBuilder
-
- clone() - Method in class ec.gp.GPProblem
-
- clone() - Method in class ec.gp.GPTree
-
Deep-clones the tree.
- clone() - Method in class ec.gp.koza.CrossoverPipeline
-
- clone() - Method in class ec.gp.koza.KozaNodeSelector
-
- clone() - Method in class ec.gp.koza.MutationPipeline
-
- clone() - Method in class ec.gp.push.PushInstruction
-
- clone() - Method in class ec.gp.push.PushProblem
-
- clone() - Method in class ec.Individual
-
- clone() - Method in class ec.multiobjective.MultiObjectiveFitness
-
- clone() - Method in class ec.Problem
-
- clone() - Method in interface ec.Prototype
-
Creates a new individual cloned from a prototype,
and suitable to begin use in its own evolutionary
context.
- clone() - Method in class ec.pso.Particle
-
- clone() - Method in class ec.rule.breed.RuleCrossoverPipeline
-
- clone() - Method in class ec.rule.Rule
-
- clone() - Method in class ec.rule.RuleIndividual
-
- clone() - Method in class ec.rule.RuleSet
-
- clone() - Method in class ec.select.MultiSelection
-
- clone() - Method in class ec.Species
-
- clone() - Method in class ec.util.MersenneTwister
-
- clone() - Method in class ec.util.MersenneTwisterFast
-
- clone() - Method in class ec.vector.BitVectorIndividual
-
- clone() - Method in class ec.vector.breed.ListCrossoverPipeline
-
- clone() - Method in class ec.vector.breed.MultipleVectorCrossoverPipeline
-
- clone() - Method in class ec.vector.breed.VectorCrossoverPipeline
-
- clone() - Method in class ec.vector.ByteVectorIndividual
-
- clone() - Method in class ec.vector.DoubleVectorIndividual
-
- clone() - Method in class ec.vector.FloatVectorIndividual
-
- clone() - Method in class ec.vector.Gene
-
- clone() - Method in class ec.vector.GeneVectorIndividual
-
- clone() - Method in class ec.vector.IntegerVectorIndividual
-
- clone() - Method in class ec.vector.LongVectorIndividual
-
- clone() - Method in class ec.vector.ShortVectorIndividual
-
- cloneGenes(Object) - Method in class ec.vector.GeneVectorIndividual
-
- cloneGenes(Object) - Method in class ec.vector.VectorIndividual
-
Clones the genes in pieces, and replaces the genes with their copies.
- clonePipelineAndPopulation - Variable in class ec.simple.SimpleBreeder
-
- cloneProblem - Variable in class ec.simple.SimpleEvaluator
-
- cloneReplacing() - Method in class ec.gp.GPNode
-
- cloneReplacing(GPNode, GPNode) - Method in class ec.gp.GPNode
-
Deep-clones the tree rooted at this node, and returns the entire
copied tree.
- cloneReplacing(GPNode[], GPNode[]) - Method in class ec.gp.GPNode
-
Deep-clones the tree rooted at this node, and returns the entire
copied tree.
- cloneReplacingAtomic(GPNode, GPNode) - Method in class ec.gp.GPNode
-
Clones a new subtree, but with the single node oldNode
(which may or may not be in the subtree)
replaced with a newNode (not a clone of newNode).
- cloneReplacingAtomic(GPNode[], GPNode[]) - Method in class ec.gp.GPNode
-
Clones a new subtree, but with each node in oldNodes[] respectively
(which may or may not be in the subtree) replaced with
the equivalent
nodes in newNodes[] (and not clones).
- cloneReplacingNoSubclone(GPNode, GPNode) - Method in class ec.gp.GPNode
-
Deep-clones the tree rooted at this node, and returns the entire
copied tree.
- close() - Method in class ec.util.Output
-
Closes the logs -- ONLY call this if you are preparing to quit
- closeContacts(EvolutionState, int) - Method in class ec.eval.MasterProblem
-
Gracefully close contacts with the slaves
- closeContacts(EvolutionState, int) - Method in class ec.Evaluator
-
Called to shut down remote evaluation network contacts when the run is completed.
- closeContacts(EvolutionState, int) - Method in class ec.exchange.InterPopulationExchange
-
Closes contacts with other processes, if that's what you're doing.
- closeContacts(EvolutionState, int) - Method in class ec.exchange.IslandExchange
-
Closes contacts with other processes, if that's what you're doing.
- closeContacts(EvolutionState, int) - Method in class ec.Exchanger
-
Closes contacts with other processes, if that's what you're doing.
- closeContacts(EvolutionState, int) - Method in class ec.gp.ge.GEProblem
-
- closeContacts(EvolutionState, int) - Method in class ec.Problem
-
Called to shut down remote evaluation network contacts when the run is completed.
- closeContacts(EvolutionState, int) - Method in class ec.simple.SimpleExchanger
-
Doesn't do anything.
- CMAESBreeder - Class in ec.eda
-
CMAESBreeder is a Breeder which overrides the breedPopulation method
to first update CMA-ES's internal distribution, then replace all the
individuals in the population with new samples generated from the
distribution.
- CMAESBreeder() - Constructor for class ec.eda.CMAESBreeder
-
- CMAESInitializer - Class in ec.eda
-
CMAESInitializer is a SimpleInitializer which ensures that the subpopulations are all set to the provided
or computed lambda values.
- CMAESInitializer() - Constructor for class ec.eda.CMAESInitializer
-
- CMAESSpecies - Class in ec.eda
-
CMAESSpecies is a FloatVectorSpecies which implements a faithful version of the
CMA-ES algorithm.
- CMAESSpecies() - Constructor for class ec.eda.CMAESSpecies
-
- cmu - Variable in class ec.eda.CMAESSpecies
-
The c_{\mu} rank-mu update learning rate.
- Code - Class in ec.util
-
Code provides some simple wrapper functions for encoding and decoding
basic data types for storage in a pseudo-Java source code strings
format.
- Code() - Constructor for class ec.util.Code
-
- combine(EvolutionState, Fitness[], Fitness) - Method in class ec.eval.MetaProblem
-
Combines fitness results from multiple runs into a final Fitness.
- COMMENT - Static variable in class ec.gp.ge.GrammarParser
-
- compareTo(Object) - Method in class ec.Fitness
-
Returns -1 if I am FITTER than the other Fitness, 1 if I am LESS FIT than the other Fitness,
and 0 if we are equivalent.
- compareTo(Object) - Method in class ec.Individual
-
Returns -1 if I am BETTER in some way than the other Individual, 1 if the other Individual is BETTER than me,
and 0 if we are equivalent.
- compareTo(Object) - Method in class ec.rule.Rule
-
This function replaces the old gt and lt functions that Rule used to require
as it implemented the SortComparator interface.
- comparison - Variable in class ec.es.MuCommaLambdaBreeder
-
- compatibleWith(GPInitializer, GPType) - Method in class ec.gp.GPAtomicType
-
- compatibleWith(GPInitializer, GPType) - Method in class ec.gp.GPSetType
-
- compatibleWith(GPInitializer, GPType) - Method in class ec.gp.GPType
-
Am I compatible with ("fit" with) t? For two atomic
types, this is done by direct pointer equality.
- CompetitiveEvaluator - Class in ec.coevolve
-
CompetitiveEvaluator.java
- CompetitiveEvaluator() - Constructor for class ec.coevolve.CompetitiveEvaluator
-
- compress - Variable in class ec.simple.SimpleStatistics
-
Should we compress the file?
- compressedCommunication - Variable in class ec.exchange.IslandExchange
-
whether the communication is compressed or not
- computeAuxiliaryData(EvolutionState, Individual[]) - Method in class ec.multiobjective.spea2.SPEA2Evaluator
-
Computes the strength of individuals, then the raw fitness (wimpiness) and kth-closest sparsity
measure.
- computeNonterminalSelectionProbabilities(int) - Method in class ec.gp.build.PTCFunctionSet
-
- computePercentages() - Method in class ec.gp.build.Uniform
-
- computeSubpopulationLength(EvolutionState, Population, int, int) - Method in class ec.simple.SimpleBreeder
-
Elites are often stored in the top part of the subpopulation; this function returns what
part of the subpopulation contains individuals to replace with newly-bred ones
(up to but not including the elites).
- computeValidationData(EvolutionState, VectorIndividual[], int) - Method in class ec.vector.breed.ListCrossoverPipeline
-
A hook called by ListCrossoverPipeline to allow subclasses to prepare for additional validation testing.
- Console - Class in ec.display
-
- Console(String[]) - Constructor for class ec.display.Console
-
- Console(GraphicsConfiguration, String[]) - Constructor for class ec.display.Console
-
- Console(String, String[]) - Constructor for class ec.display.Console
-
- Console(String, GraphicsConfiguration, String[]) - Constructor for class ec.display.Console
-
- constraintNumber - Variable in class ec.gp.GPNodeConstraints
-
The byte value of the constraints -- we can only have 256 of them
- constraintNumber - Variable in class ec.gp.GPTreeConstraints
-
The byte value of the constraints -- we can only have 256 of them
- constraintNumber - Variable in class ec.rule.RuleConstraints
-
The byte value of the constraints -- we can only have 256 of them
- constraintNumber - Variable in class ec.rule.RuleSetConstraints
-
The byte value of the constraints -- we can only have 256 of them
- constraints - Variable in class ec.gp.GPNode
-
The GPNode's constraints.
- constraints(GPInitializer) - Method in class ec.gp.GPNode
-
- constraints - Variable in class ec.gp.GPTree
-
constraints on the GPTree -- don't access the constraints through
this variable -- use the constraints() method instead, which will give
the actual constraints object.
- constraints(GPInitializer) - Method in class ec.gp.GPTree
-
- constraints - Variable in class ec.rule.Rule
-
An index to a RuleConstraints
- constraints(RuleInitializer) - Method in class ec.rule.Rule
-
- constraints - Variable in class ec.rule.RuleSet
-
An index to a RuleSetConstraints
- constraints(RuleInitializer) - Method in class ec.rule.RuleSet
-
- constraintsFor(String, EvolutionState) - Static method in class ec.gp.GPNodeConstraints
-
You must guarantee that after calling constraintsFor(...) one or
several times, you call state.output.exitIfErrors() once.
- constraintsFor(String, EvolutionState) - Static method in class ec.gp.GPTreeConstraints
-
You must guarantee that after calling constraintsFor(...) one or
several times, you call state.output.exitIfErrors() once.
- constraintsFor(String, EvolutionState) - Static method in class ec.rule.RuleConstraints
-
You must guarantee that after calling constraintsFor(...) one or
several times, you call state.output.exitIfErrors() once.
- constraintsFor(String, EvolutionState) - Static method in class ec.rule.RuleSetConstraints
-
You must guarantee that after calling constraintsFor(...) one or
several times, you call state.output.exitIfErrors() once.
- consumed(EvolutionState, GEIndividual, int) - Method in class ec.gp.ge.GESpecies
-
Returns the number of elements consumed from the GEIndividual array to produce
the tree, else returns -1 if an error occurs, specifically if all elements were
consumed and the tree had still not been completed.
- contains(GPNode) - Method in class ec.gp.GPNode
-
Returns true if the subtree rooted at this node contains subnode.
- contains(boolean[], boolean) - Method in class ec.vector.VectorSpecies
-
Utility method: returns the first array slot which contains the given value, else -1.
- contains(long[], long) - Method in class ec.vector.VectorSpecies
-
Utility method: returns the first array slot which contains the given value, else -1.
- contains(int[], int) - Method in class ec.vector.VectorSpecies
-
Utility method: returns the first array slot which contains the given value, else -1.
- contains(double[], double) - Method in class ec.vector.VectorSpecies
-
Utility method: returns the first array slot which contains the given value, else -1.
- context - Variable in class ec.Fitness
-
Auxiliary variable, used by coevolutionary processes, to store the individuals
involved in producing this given Fitness value.
- context_proto - Variable in class ec.gp.ADFStack
-
- contextIsBetterThan(Fitness) - Method in class ec.Fitness
-
Given another Fitness,
returns true if the trial which produced my current context is "better" in fitness than
the trial which produced his current context, and thus should be retained in lieu of his.
- contributors - Static variable in class ec.util.Version
-
- contributors2 - Static variable in class ec.util.Version
-
- contributors3 - Static variable in class ec.util.Version
-
- contributors4 - Static variable in class ec.util.Version
-
- contributors5 - Static variable in class ec.util.Version
-
- contributors6 - Static variable in class ec.util.Version
-
- ControlPanel - Class in ec.display
-
- ControlPanel(Console) - Constructor for class ec.display.ControlPanel
-
This is the default constructor
- copy(Serializable) - Static method in class ec.util.DataPipe
-
A poor-man's clone for serializable but not cloneable objects:
serializes an object to the pipe, then deserializes it.
- copyNoClone(RuleSet) - Method in class ec.rule.RuleSet
-
Clears out existing rules, and loads the rules from the other ruleset without cloning them.
- copyright - Static variable in class ec.util.Version
-
- copyTo(GPData) - Method in class ec.gp.GPData
-
Modifies gpd so that gpd is equivalent to us.
- count - Variable in class ec.es.MuCommaLambdaBreeder
-
Modified by multiple threads, don't fool with this
- countdown - Variable in class ec.evolve.RandomRestarts
-
- Cr - Variable in class ec.de.DEBreeder
-
Probability of crossover per gene
- CR_UNSPECIFIED - Static variable in class ec.de.DEBreeder
-
- createIndividual(EvolutionState, int, int, int) - Method in class ec.de.Best1BinDEBreeder
-
- createIndividual(EvolutionState, int, int, int) - Method in class ec.de.DEBreeder
-
- createIndividual(EvolutionState, int, int, int) - Method in class ec.de.Rand1EitherOrDEBreeder
-
- crossover(EvolutionState, DoubleVectorIndividual, DoubleVectorIndividual, int) - Method in class ec.de.DEBreeder
-
Crosses over child with target, storing the result in child and returning it.
- crossoverDistributionIndex - Variable in class ec.vector.VectorSpecies
-
What should the SBX distribution index be?
- CrossoverPipeline - Class in ec.gp.koza
-
CrossoverPipeline is a GPBreedingPipeline which performs a strongly-typed
version of
Koza-style "Subtree Crossover".
- CrossoverPipeline() - Constructor for class ec.gp.koza.CrossoverPipeline
-
- crossoverProbability - Variable in class ec.vector.VectorSpecies
-
Probability that a gene will cross over -- ONLY used in V_ANY_POINT crossover
- crossoverType - Variable in class ec.vector.breed.ListCrossoverPipeline
-
- crossoverType - Variable in class ec.vector.VectorSpecies
-
What kind of crossover do we have?
- cs - Variable in class ec.eda.CMAESSpecies
-
The c_{\sigma} mutation rate evolution path learning rate.
- currentDatabase - Variable in class ec.eval.MetaProblem
-
This points to the database presently used by the underlying (base-level) evolutionary computation system.
- currentSize - Variable in class ec.breed.BufferedBreedingPipeline
-
- customInstructions - Variable in class ec.gp.push.Terminal
-
A list of custom PushInstructions I can be set to.
- ec - package ec
-
- ec.breed - package ec.breed
-
- ec.coevolve - package ec.coevolve
-
- ec.de - package ec.de
-
- ec.display - package ec.display
-
- ec.display.chart - package ec.display.chart
-
- ec.display.portrayal - package ec.display.portrayal
-
- ec.eda - package ec.eda
-
- ec.es - package ec.es
-
- ec.eval - package ec.eval
-
- ec.evolve - package ec.evolve
-
- ec.exchange - package ec.exchange
-
- ec.gp - package ec.gp
-
- ec.gp.breed - package ec.gp.breed
-
- ec.gp.build - package ec.gp.build
-
- ec.gp.ge - package ec.gp.ge
-
- ec.gp.koza - package ec.gp.koza
-
- ec.gp.push - package ec.gp.push
-
- ec.multiobjective - package ec.multiobjective
-
- ec.multiobjective.nsga2 - package ec.multiobjective.nsga2
-
- ec.multiobjective.spea2 - package ec.multiobjective.spea2
-
- ec.parsimony - package ec.parsimony
-
- ec.pso - package ec.pso
-
- ec.rule - package ec.rule
-
- ec.rule.breed - package ec.rule.breed
-
- ec.select - package ec.select
-
- ec.simple - package ec.simple
-
- ec.spatial - package ec.spatial
-
- ec.steadystate - package ec.steadystate
-
- ec.util - package ec.util
-
- ec.vector - package ec.vector
-
- ec.vector.breed - package ec.vector.breed
-
- ECDefaults - Class in ec
-
- ECDefaults() - Constructor for class ec.ECDefaults
-
- EDADefaults - Class in ec.eda
-
EDADefaults is the basic defaults class for the eda package.
- EDADefaults() - Constructor for class ec.eda.EDADefaults
-
- elite - Variable in class ec.simple.SimpleBreeder
-
An array[subpop] of the number of elites to keep for that subpopulation
- eliteFrac - Variable in class ec.simple.SimpleBreeder
-
- emptyClone() - Method in interface ec.Group
-
Returns a copy of the object just as it had been
immediately after Setup was called on it (or on
an ancestor object).
- emptyClone() - Method in class ec.Population
-
Returns an instance of Population just like it had been before it was
populated with individuals.
- emptyClone() - Method in class ec.Subpopulation
-
Returns an instance of Subpopulation just like it had been before it was
populated with individuals.
- enableControls() - Method in class ec.display.ControlPanel
-
- encode() - Method in class ec.gp.ERC
-
Encodes data from the ERC, using ec.util.Code.
- encode() - Method in class ec.gp.push.Terminal
-
- encode(boolean) - Static method in class ec.util.Code
-
Encodes a boolean.
- encode(byte) - Static method in class ec.util.Code
-
Encodes a byte.
- encode(char) - Static method in class ec.util.Code
-
Encodes a character.
- encode(short) - Static method in class ec.util.Code
-
Encodes a short.
- encode(int) - Static method in class ec.util.Code
-
Encodes an int.
- encode(long) - Static method in class ec.util.Code
-
Encodes a long.
- encode(float) - Static method in class ec.util.Code
-
Encodes a float.
- encode(double) - Static method in class ec.util.Code
-
Encodes a double.
- encode(String) - Static method in class ec.util.Code
-
Encodes a String.
- enteringInitialPopulationStatistics(SteadyStateEvolutionState) - Method in class ec.Statistics
-
STEADY-STATE: called when we created an empty initial Population.
- enteringInitialPopulationStatistics(SteadyStateEvolutionState) - Method in interface ec.steadystate.SteadyStateStatisticsForm
-
Called when we created an empty initial Population.
- enteringSteadyStateStatistics(int, SteadyStateEvolutionState) - Method in class ec.Statistics
-
STEADY-STATE: called when a given Subpopulation is entering the Steady-State.
- enteringSteadyStateStatistics(int, SteadyStateEvolutionState) - Method in interface ec.steadystate.SteadyStateStatisticsForm
-
Called when we have filled the initial population and are entering the steady state.
- enumerateGrammarTree(GrammarNode) - Method in class ec.gp.ge.GrammarParser
-
Run BFS to enumerate the whole grammar tree into all necessary
indices lists/hash-maps, we *need* to run BFS because the decoding of
the "GE array to tree" works in a BFS fashion, so we need to stick with that;
After enumeration, we will have four data-structures like these --
(1) productionRuleList (a flattened grammar tree):
grammar-tree ==> {rule-0, rule-1, ,,, rule-(n-1)}
(2) ruleToIndex:
rule-0 --> 0
rule-1 --> 1
,
,
rule-(n-1) --> (n-1)
(3) indexToRule (reverse of ruleToIndex):
0 --> rule-0
1 --> rule-1
,
,
n-1 --> rule-(n-1)
and then, last but not the least, the relative rule index --
(4) absIndexToRelIndex:
if we have two rules like "
-> | " and " -> | " then,
[rule] [absIndex] [relIndex]
-> --> [0] --> [0]
-> --> [1] --> [1]
-> --> [2] --> [0]
-> --> [3] --> [1] etc,
- equals(Object) - Method in class ec.gp.ge.GrammarNode
-
This is needed when we use a GrammarNode as a "key"
in hash-map, see GrammarParser.java for details.
- EQUALS - Static variable in class ec.gp.ge.GrammarParser
-
- equals(Object) - Method in class ec.gp.GPIndividual
-
- equals(Object) - Method in class ec.Individual
-
Returns true if I am genetically "equal" to ind.
- equals(Object) - Method in class ec.pso.Particle
-
- equals(Object) - Method in class ec.rule.Rule
-
Unlike the standard form for Java, this function should return true if this
rule is "genetically identical" to the other rule.
- equals(Object) - Method in class ec.rule.RuleIndividual
-
- equals(Object) - Method in class ec.rule.RuleSet
-
- equals(Object) - Method in class ec.util.ReflectedObject
-
- equals(Object) - Method in class ec.vector.BitVectorIndividual
-
- equals(Object) - Method in class ec.vector.ByteVectorIndividual
-
- equals(Object) - Method in class ec.vector.DoubleVectorIndividual
-
- equals(Object) - Method in class ec.vector.FloatVectorIndividual
-
- equals(Object) - Method in class ec.vector.Gene
-
Unlike the standard form for Java, this function should return true if this
gene is "genetically identical" to the other gene.
- equals(Object) - Method in class ec.vector.GeneVectorIndividual
-
- equals(Object) - Method in class ec.vector.IntegerVectorIndividual
-
- equals(Object) - Method in class ec.vector.LongVectorIndividual
-
- equals(Object) - Method in class ec.vector.ShortVectorIndividual
-
- equivalentTo(Fitness) - Method in class ec.Fitness
-
Should return true if this fitness is in the same equivalence class
as _fitness, that is, neither is clearly better or worse than the
other.
- equivalentTo(Fitness) - Method in class ec.gp.koza.KozaFitness
-
- equivalentTo(Fitness) - Method in class ec.multiobjective.MultiObjectiveFitness
-
Returns true if I'm equivalent in fitness (neither better nor worse) to
_fitness.
- equivalentTo(Fitness) - Method in class ec.multiobjective.nsga2.NSGA2MultiObjectiveFitness
-
- equivalentTo(Fitness) - Method in class ec.multiobjective.spea2.SPEA2MultiObjectiveFitness
-
The selection criteria in SPEA2 uses the computed fitness, and not
pareto dominance.
- equivalentTo(Fitness) - Method in class ec.simple.SimpleFitness
-
- ERC - Class in ec.gp
-
ERC is an abstract GPNode which implements Ephemeral Random Constants,
as described in Koza I.
- ERC() - Constructor for class ec.gp.ERC
-
- ERC_NAMES - Static variable in class ec.gp.push.Terminal
-
- ERC_PREAMBLE - Static variable in class ec.gp.ge.GEIndividual
-
- ERCBank - Variable in class ec.gp.ge.GESpecies
-
All the ERCs created so far, the ERCs are mapped as,
"key --> list of ERC nodes", where the key = (genome[i] - minGene[i]);
The ERCBank is "static", beacause we need one identical copy
for all the individuals; Moreover, this copy may be sent to
other sub-populations as well.
- error(String) - Method in class ec.util.Output
-
Posts a simple error.
- error(String, Parameter) - Method in class ec.util.Output
-
Posts a simple error.
- error(String, Parameter, Parameter) - Method in class ec.util.Output
-
Posts a simple error.
- errorAboutNoNodeWithType(GPType, EvolutionState) - Method in class ec.gp.GPNodeBuilder
-
Issues a fatal error that no node (nonterminal or terminal) was found with a return type of the given type, and that an algorithm
had requested one.
- errorInfo() - Method in class ec.gp.GPNode
-
A convenience function for identifying a GPNode in an error message
- ESDefaults - Class in ec.es
-
- ESDefaults() - Constructor for class ec.es.ESDefaults
-
- ESSelection - Class in ec.es
-
ESSelection is a special SelectionMethod designed to be used with
evolutionary strategies-type breeders.
- ESSelection() - Constructor for class ec.es.ESSelection
-
- eval(EvolutionState, int, GPData, ADFStack, GPIndividual, Problem) - Method in class ec.gp.ADF
-
- eval(EvolutionState, int, GPData, ADFStack, GPIndividual, Problem) - Method in class ec.gp.ADFArgument
-
- eval(EvolutionState, int, GPData, ADFStack, GPIndividual, Problem) - Method in class ec.gp.ADM
-
- eval(EvolutionState, int, GPData, ADFStack, GPIndividual, Problem) - Method in class ec.gp.GPNode
-
Evaluates the node with the given thread, state, individual, problem, and stack.
- eval(EvolutionState, int, GPData, ADFStack, GPIndividual, Problem) - Method in class ec.gp.push.Nonterminal
-
- eval(EvolutionState, int, GPData, ADFStack, GPIndividual, Problem) - Method in class ec.gp.push.Terminal
-
- evalNRandomOneWay(EvolutionState, int[], int[], Individual[], int, GroupedProblemForm) - Method in class ec.coevolve.CompetitiveEvaluator
-
- evalNRandomOneWayPopChunk(EvolutionState, int, int, int, Individual[], int, GroupedProblemForm) - Method in class ec.coevolve.CompetitiveEvaluator
-
- evalNRandomTwoWay(EvolutionState, int[], int[], Individual[], int, GroupedProblemForm) - Method in class ec.coevolve.CompetitiveEvaluator
-
- evalNRandomTwoWayPopChunk(EvolutionState, int, int, int, Individual[], int, GroupedProblemForm) - Method in class ec.coevolve.CompetitiveEvaluator
-
- evalPopChunk(EvolutionState, int[], int[], int, SimpleProblemForm) - Method in class ec.simple.SimpleEvaluator
-
A private helper function for evaluatePopulation which evaluates a chunk
of individuals in a subpopulation for a given thread.
- evalRoundRobin(EvolutionState, int[], int[], Individual[], int, GroupedProblemForm) - Method in class ec.coevolve.CompetitiveEvaluator
-
- evalRoundRobinPopChunk(EvolutionState, int, int, int, Individual[], int, GroupedProblemForm) - Method in class ec.coevolve.CompetitiveEvaluator
-
A private helper function for evalutatePopulation which evaluates a chunk
of individuals in a subpopulation for a given thread.
- evalSingleElimination(EvolutionState, Individual[], int, GroupedProblemForm) - Method in class ec.coevolve.CompetitiveEvaluator
-
- evalthreads - Variable in class ec.EvolutionState
-
The requested number of threads to be used in evaluation, excepting perhaps a "parent" thread which gathers the other threads.
- evaluate(EvolutionState, Individual[], boolean[], boolean, int[], int) - Method in interface ec.coevolve.GroupedProblemForm
-
Evaluates the individuals found in ind together.
- evaluate(EvolutionState, Individual, int, int) - Method in class ec.eval.MasterProblem
-
- evaluate(EvolutionState, Individual[], boolean[], boolean, int[], int) - Method in class ec.eval.MasterProblem
-
- evaluate(EvolutionState, Individual, int, int) - Method in class ec.eval.MetaProblem
-
- evaluate(EvolutionState, int, GPData, ADFStack, GPIndividual, Problem, int) - Method in class ec.gp.ADFContext
-
Evaluates the argument number in the current context
- evaluate(EvolutionState, Individual[], boolean[], boolean, int[], int) - Method in class ec.gp.ge.GEProblem
-
Default version assumes that every individual is a GEIndividual.
- evaluate(EvolutionState, Individual, int, int) - Method in class ec.gp.ge.GEProblem
-
- evaluate(EvolutionState, Individual, int, int) - Method in interface ec.simple.SimpleProblemForm
-
Evaluates the individual in ind, if necessary (perhaps
not evaluating them if their evaluated flags are true),
and sets their fitness appropriately.
- evaluated - Variable in class ec.Individual
-
Has the individual been evaluated and its fitness determined yet?
- EVALUATED_PREAMBLE - Static variable in class ec.Individual
-
A string appropriate to put in front of whether or not the individual has been printed.
- evaluatedIndividualAvailable() - Method in class ec.eval.MasterProblem
-
This will only return true if (1) the EvolutionState is a SteadyStateEvolutionState and
(2) an individual has returned from the system.
- evaluatedIndividualAvailable() - Method in class ec.eval.SlaveMonitor
-
- evaluateGroupedProblemForm(EvolutionState, boolean, DataInputStream, DataOutputStream) - Static method in class ec.eval.Slave
-
- evaluateIndividual(EvolutionState, Individual, int) - Method in class ec.steadystate.SteadyStateEvaluator
-
Submits an individual to be evaluated by the Problem, and adds it and its subpopulation to the queue.
- evaluatePopulation(EvolutionState) - Method in class ec.coevolve.CompetitiveEvaluator
-
An evaluator that performs coevolutionary evaluation.
- evaluatePopulation(EvolutionState) - Method in class ec.coevolve.MultiPopCoevolutionaryEvaluator
-
- evaluatePopulation(EvolutionState) - Method in class ec.de.DEEvaluator
-
- evaluatePopulation(EvolutionState) - Method in class ec.Evaluator
-
Evaluates the fitness of an entire population.
- evaluatePopulation(EvolutionState) - Method in class ec.multiobjective.nsga2.NSGA2Evaluator
-
Evaluates the population, then builds the archive and reduces the population to just the archive.
- evaluatePopulation(EvolutionState) - Method in class ec.multiobjective.spea2.SPEA2Evaluator
-
- evaluatePopulation(EvolutionState) - Method in class ec.simple.SimpleEvaluator
-
A simple evaluator that doesn't do any coevolutionary
evaluation.
- evaluateSimpleProblemForm(EvolutionState, boolean, DataInputStream, DataOutputStream, String[]) - Static method in class ec.eval.Slave
-
- evaluations - Variable in class ec.steadystate.SteadyStateEvolutionState
-
How many evaluations have we run so far?
- Evaluator - Class in ec
-
An Evaluator is a singleton object which is responsible for the
evaluation process during the course of an evolutionary run.
- Evaluator() - Constructor for class ec.Evaluator
-
- evaluator - Variable in class ec.EvolutionState
-
The population evaluator, a singleton object.
- EvolutionState - Class in ec
-
An EvolutionState object is a singleton object which holds the entire
state of an evolutionary run.
- EvolutionState() - Constructor for class ec.EvolutionState
-
This will be called to create your evolution state; immediately
after the constructor is called,
the parameters, random, and output fields will be set
for you.
- EvolutionStateEvent - Class in ec.display
-
- EvolutionStateEvent(Object) - Constructor for class ec.display.EvolutionStateEvent
-
- EvolutionStateListener - Interface in ec.display
-
- evolve() - Method in class ec.EvolutionState
-
- Evolve - Class in ec
-
Evolve is the main entry class for an evolutionary computation run.
- Evolve() - Constructor for class ec.Evolve
-
- evolve() - Method in class ec.exchange.IslandExchange
-
- evolve() - Method in class ec.simple.SimpleEvolutionState
-
- evolve() - Method in class ec.steadystate.SteadyStateEvolutionState
-
- exchanger - Variable in class ec.EvolutionState
-
The population exchanger, a singleton object.
- Exchanger - Class in ec
-
The Exchanger is a singleton object whose job is to (optionally)
perform individual exchanges between subpopulations in the run,
or exchange individuals with other concurrent evolutionary run processes,
using sockets or whatever.
- Exchanger() - Constructor for class ec.Exchanger
-
- Execute(Interpreter) - Method in class ec.gp.push.PushInstruction
-
- executeProgram(Program, Interpreter, int) - Method in class ec.gp.push.PushProblem
-
Executes the given program for up to maxSteps steps.
- exists(Parameter) - Method in class ec.util.ParameterDatabase
-
- exists(Parameter, Parameter) - Method in class ec.util.ParameterDatabase
-
Returns true if either parameter or defaultParameter exists in the
database
- exitIfErrors() - Method in class ec.util.Output
-
Exits with a fatal error if the error flag has been raised.
- expectedChildren() - Method in class ec.gp.ADFArgument
-
- expectedChildren() - Method in class ec.gp.ERC
-
Usually ERCs don't have children, and this default implementation makes certain of it.
- expectedChildren() - Method in class ec.gp.GPNode
-
Returns the number of children this node expects to have.
- expectedChildren() - Method in class ec.gp.push.Terminal
-
- expectedSize - Variable in class ec.gp.build.PTC1
-
The default expected tree size for PTC1
- extraBehavior - Variable in class ec.Subpopulation
-
What is our fill behavior beyond files?
- gatherExtraPopStatistics(EvolutionState, int) - Method in class ec.simple.SimpleShortStatistics
-
- gatherExtraSubpopStatistics(EvolutionState, int, int) - Method in class ec.gp.koza.KozaShortStatistics
-
- gatherExtraSubpopStatistics(EvolutionState, int, int) - Method in class ec.simple.SimpleShortStatistics
-
- gatherFirstSets(GrammarNode, GrammarNode) - Method in class ec.gp.ge.GrammarParser
-
Generate the FIRST-SET for each production rule and store them in the
global hash-table, this runs a DFS on the grammar tree, the returned ArrayList
is discarded and the FIRST-SETs are organized in a hash-map called
"ruleToFirstSet" as follows --
rule-0 --> {FIRST-SET-0}
rule-1 --> {FIRST-SET-1}
,
,
rule-(n-1) --> {FIRST-SET-(n-1)}
- gatherFollowSets(GrammarNode, GrammarNode) - Method in class ec.gp.ge.GrammarParser
-
We do not have any example grammar to test with FOLLOW-SETs,
so the FOLLOW-SET is empty, we need to test with a grammar
that contains post-fix notations;
this needs to be implemented properly with a new grammar.
- gatherNodeString(EvolutionState, int, GPNode, int) - Method in class ec.gp.ge.GESpecies
-
Used by the above function
- gatherPredictSets(GrammarNode, GrammarNode) - Method in class ec.gp.ge.GrammarParser
-
Populate the PREDICT-SET from the FIRST-SETs and the FOLLOW-SETs,
as we do not have FOLLOW-SET, so FIRST-SET == PREDICT-SET;
this needs to be implemented, when the FOLLOW-SETs are done properly.
- gaussMutationStdev - Variable in class ec.vector.FloatVectorSpecies
-
Standard deviation for Gaussian Mutation, per gene.
- gaussMutationStdev(int) - Method in class ec.vector.FloatVectorSpecies
-
- GEDefaults - Class in ec.gp.ge
-
A static class that returns the base for "default values" which GE-style
operators use, rather than making the user specify them all on a per-
species basis.
- GEDefaults() - Constructor for class ec.gp.ge.GEDefaults
-
- GEIndividual - Class in ec.gp.ge
-
GEIndividual is a simple subclass of IntegerVectorIndividual which not only prints out (for humans)
the Individual as a int vector but also prints out the Individual's tree representation.
- GEIndividual() - Constructor for class ec.gp.ge.GEIndividual
-
- Gene - Class in ec.vector
-
Gene is an abstract superclass of objects which may be used in
the genome array of GeneVectorIndividuals.
- Gene() - Constructor for class ec.vector.Gene
-
- GeneDuplicationPipeline - Class in ec.vector.breed
-
GeneDuplicationPipeline is designed to duplicate a sequence of genes from the chromosome and append
them to the end of the chromosome.
- GeneDuplicationPipeline() - Constructor for class ec.vector.breed.GeneDuplicationPipeline
-
- genePrototype - Variable in class ec.vector.GeneVectorSpecies
-
- generateMax - Variable in class ec.breed.GenerationSwitchPipeline
-
- generateMax - Variable in class ec.breed.MultiBreedingPipeline
-
- generation - Variable in class ec.EvolutionState
-
The current generation of the population in the run.
- generationBoundary - Variable in class ec.steadystate.SteadyStateEvolutionState
-
Did we just start a new generation?
- generationBoundaryStatistics(EvolutionState) - Method in class ec.Statistics
-
STEADY-STATE: called each time the generation count increments
- generationBoundaryStatistics(EvolutionState) - Method in interface ec.steadystate.SteadyStateStatisticsForm
-
Called when the generation count increments
- generationSize - Variable in class ec.steadystate.SteadyStateEvolutionState
-
how big is a generation? Set to the size of subpopulation 0 of the initial population.
- generationSwitch - Variable in class ec.breed.GenerationSwitchPipeline
-
- GenerationSwitchPipeline - Class in ec.breed
-
GenerationSwitchPipeline is a simple BreedingPipeline which switches its source depending
on the generation.
- GenerationSwitchPipeline() - Constructor for class ec.breed.GenerationSwitchPipeline
-
- GeneVectorIndividual - Class in ec.vector
-
GeneVectorIndividual is a VectorIndividual whose genome is an array of Genes.
- GeneVectorIndividual() - Constructor for class ec.vector.GeneVectorIndividual
-
- GeneVectorSpecies - Class in ec.vector
-
GeneVectorSpecies is a subclass of VectorSpecies with special
constraints for GeneVectorIndividuals.
- GeneVectorSpecies() - Constructor for class ec.vector.GeneVectorSpecies
-
- genome - Variable in class ec.vector.BitVectorIndividual
-
- genome - Variable in class ec.vector.ByteVectorIndividual
-
- genome - Variable in class ec.vector.DoubleVectorIndividual
-
- genome - Variable in class ec.vector.FloatVectorIndividual
-
- genome - Variable in class ec.vector.GeneVectorIndividual
-
- genome - Variable in class ec.vector.IntegerVectorIndividual
-
- genome - Variable in class ec.vector.LongVectorIndividual
-
- genome - Variable in class ec.vector.ShortVectorIndividual
-
- genomeIncreaseProbability - Variable in class ec.vector.VectorSpecies
-
With what probability would our genome be at least 1 larger than it is now during initialization?
- genomeLength() - Method in class ec.vector.BitVectorIndividual
-
- genomeLength() - Method in class ec.vector.ByteVectorIndividual
-
- genomeLength() - Method in class ec.vector.DoubleVectorIndividual
-
- genomeLength() - Method in class ec.vector.FloatVectorIndividual
-
- genomeLength() - Method in class ec.vector.GeneVectorIndividual
-
- genomeLength() - Method in class ec.vector.IntegerVectorIndividual
-
- genomeLength() - Method in class ec.vector.LongVectorIndividual
-
- genomeLength() - Method in class ec.vector.ShortVectorIndividual
-
- genomeLength() - Method in class ec.vector.VectorIndividual
-
Returns the length of the gene array.
- genomeResizeAlgorithm - Variable in class ec.vector.VectorSpecies
-
How should we reset the genome?
- genomeSize - Variable in class ec.vector.VectorSpecies
-
How big of a genome should we create on initialization?
- genotypeToString() - Method in class ec.Individual
-
Print to a string the genotype of the Individual in a fashion intended
to be parsed in again via parseGenotype(...).
- genotypeToString() - Method in class ec.vector.BitVectorIndividual
-
- genotypeToString() - Method in class ec.vector.ByteVectorIndividual
-
- genotypeToString() - Method in class ec.vector.DoubleVectorIndividual
-
- genotypeToString() - Method in class ec.vector.FloatVectorIndividual
-
- genotypeToString() - Method in class ec.vector.GeneVectorIndividual
-
- genotypeToString() - Method in class ec.vector.IntegerVectorIndividual
-
- genotypeToString() - Method in class ec.vector.LongVectorIndividual
-
- genotypeToString() - Method in class ec.vector.ShortVectorIndividual
-
- genotypeToStringForHumans() - Method in class ec.Individual
-
Print to a string the genotype of the Individual in a fashion readable by humans, and not intended
to be parsed in again.
- genotypeToStringForHumans() - Method in class ec.vector.BitVectorIndividual
-
- genotypeToStringForHumans() - Method in class ec.vector.ByteVectorIndividual
-
- genotypeToStringForHumans() - Method in class ec.vector.DoubleVectorIndividual
-
- genotypeToStringForHumans() - Method in class ec.vector.FloatVectorIndividual
-
- genotypeToStringForHumans() - Method in class ec.vector.GeneVectorIndividual
-
- genotypeToStringForHumans() - Method in class ec.vector.IntegerVectorIndividual
-
- genotypeToStringForHumans() - Method in class ec.vector.LongVectorIndividual
-
- genotypeToStringForHumans() - Method in class ec.vector.ShortVectorIndividual
-
- GEProblem - Class in ec.gp.ge
-
GEProblem is a special replacement for Problem which performs GE mapping.
- GEProblem() - Constructor for class ec.gp.ge.GEProblem
-
- GESpecies - Class in ec.gp.ge
-
GESpecies generates GPIndividuals from GEIndividuals through the application of a grammar parse graph
computed by the GrammarParser.
- GESpecies() - Constructor for class ec.gp.ge.GESpecies
-
- get() - Method in class ec.gp.ADFStack
-
Returns an ADFContext from the stack's reserve, or creates one
fresh if there are none in reserve.
- getArgument(int) - Method in class ec.gp.ge.GrammarFunctionNode
-
Returna given argument.
- getAuxilliaryFitnessNames() - Method in class ec.multiobjective.MultiObjectiveFitness
-
Returns auxilliary fitness value names to be printed by the statistics object.
- getAuxilliaryFitnessNames() - Method in class ec.multiobjective.nsga2.NSGA2MultiObjectiveFitness
-
- getAuxilliaryFitnessNames() - Method in class ec.multiobjective.spea2.SPEA2MultiObjectiveFitness
-
- getAuxilliaryFitnessValues() - Method in class ec.multiobjective.MultiObjectiveFitness
-
Returns auxilliary fitness values to be printed by the statistics object.
- getAuxilliaryFitnessValues() - Method in class ec.multiobjective.nsga2.NSGA2MultiObjectiveFitness
-
- getAuxilliaryFitnessValues() - Method in class ec.multiobjective.spea2.SPEA2MultiObjectiveFitness
-
- getBestSoFar() - Method in class ec.simple.SimpleShortStatistics
-
- getBestSoFar() - Method in class ec.simple.SimpleStatistics
-
- getBoolean(Parameter, Parameter, boolean) - Method in class ec.util.ParameterDatabase
-
Searches down through databases to find a given parameter; If the
parameter does not exist, defaultValue is returned.
- getChild(Object, int) - Method in class ec.util.ParameterDatabaseTreeModel
-
- getChild(int) - Method in class ec.util.ReflectedObject
-
- getChild(Object, int) - Method in class ec.util.ReflectedObject
-
- getChildCount(Object) - Method in class ec.util.ParameterDatabaseTreeModel
-
- getChildCount(Object) - Method in class ec.util.ReflectedObject
-
- getChildren() - Method in class ec.util.ReflectedObject
-
- getChoice(int) - Method in class ec.gp.ge.GrammarRuleNode
-
Returns a given choice.
- getClassForParameter(Parameter, Parameter, Class) - Method in class ec.util.ParameterDatabase
-
Searches down through databases to find a given parameter.
- getContext() - Method in class ec.Fitness
-
Treat the Individual[] you receive from this as read-only.
- getDouble(Parameter, Parameter) - Method in class ec.util.ParameterDatabase
-
- getDouble(Parameter, Parameter, double) - Method in class ec.util.ParameterDatabase
-
Searches down through databases to find a given parameter, whose value
must be a double >= minValue.
- getDouble(Parameter, Parameter, double, double) - Method in class ec.util.ParameterDatabase
-
- getDoubleWithDefault(Parameter, Parameter, double) - Method in class ec.util.ParameterDatabase
-
Searches down through databases to find a given parameter, which must be
a float.
- getDoubleWithMax(Parameter, Parameter, double, double) - Method in class ec.util.ParameterDatabase
-
Searches down through databases to find a given parameter, whose value
must be a double >= minValue and <= maxValue.
- getField(int) - Method in class ec.util.ReflectedObject
-
- getFields() - Method in class ec.util.ReflectedObject
-
- getFile(Parameter, Parameter) - Method in class ec.util.ParameterDatabase
-
Searches down through the databases to find a given parameter, whose
value must be an absolute or relative path name.
- getFloat(Parameter, Parameter) - Method in class ec.util.ParameterDatabase
-
- getFloat(Parameter, Parameter, double) - Method in class ec.util.ParameterDatabase
-
Searches down through databases to find a given parameter, whose value
must be a float >= minValue.
- getFloat(Parameter, Parameter, double, double) - Method in class ec.util.ParameterDatabase
-
- getFloatWithDefault(Parameter, Parameter, double) - Method in class ec.util.ParameterDatabase
-
Searches down through databases to find a given parameter, which must be
a float.
- getFloatWithMax(Parameter, Parameter, double, double) - Method in class ec.util.ParameterDatabase
-
Searches down through databases to find a given parameter, whose value
must be a float >= minValue and <= maxValue.
- getFlush() - Method in class ec.util.Output
-
- getGenome() - Method in class ec.vector.BitVectorIndividual
-
- getGenome() - Method in class ec.vector.ByteVectorIndividual
-
- getGenome() - Method in class ec.vector.DoubleVectorIndividual
-
- getGenome() - Method in class ec.vector.FloatVectorIndividual
-
- getGenome() - Method in class ec.vector.GeneVectorIndividual
-
- getGenome() - Method in class ec.vector.IntegerVectorIndividual
-
- getGenome() - Method in class ec.vector.LongVectorIndividual
-
- getGenome() - Method in class ec.vector.ShortVectorIndividual
-
- getGenome() - Method in class ec.vector.VectorIndividual
-
Returns the gene array.
- getGPNodePrototype() - Method in class ec.gp.ge.GrammarFunctionNode
-
Returns the prototype without cloning it first.
- getHead() - Method in class ec.gp.ge.GrammarNode
-
- getIndex(int) - Method in interface ec.spatial.Space
-
Functionality: retrieve the index for a specific threanum.
- getIndex(int) - Method in class ec.spatial.Spatial1DSubpopulation
-
- getIndexOfChild(Object, Object) - Method in class ec.util.ReflectedObject
-
- getIndexRandomNeighbor(EvolutionState, int, int) - Method in interface ec.spatial.Space
-
Input: the maximum distance for neighbors.
- getIndexRandomNeighbor(EvolutionState, int, int) - Method in class ec.spatial.Spatial1DSubpopulation
-
Returns a the index of a random neighbor.
- getInstanceForParameter(Parameter, Parameter, Class) - Method in class ec.util.ParameterDatabase
-
Searches down through databases to find a given parameter, whose value
must be a full Class name, and the class must be a descendent of but not
equal to mustCastTosuperclass .
- getInstanceForParameterEq(Parameter, Parameter, Class) - Method in class ec.util.ParameterDatabase
-
Searches down through databases to find a given parameter, whose value
must be a full Class name, and the class must be a descendent, or equal
to, mustCastTosuperclass .
- getInt(Parameter, Parameter) - Method in class ec.util.ParameterDatabase
-
Searches down through databases to find a given parameter, whose value
must be an integer.
- getInt(Parameter, Parameter, int) - Method in class ec.util.ParameterDatabase
-
Searches down through databases to find a given parameter, whose value
must be an integer >= minValue.
- getInterpreter(EvolutionState, GPIndividual, int) - Method in class ec.gp.push.PushProblem
-
Builds a Push Interpreter suitable for interpreting the Program given in getProgram().
- getIntWithDefault(Parameter, Parameter, int) - Method in class ec.util.ParameterDatabase
-
Searches down through databases to find a given parameter, which must be
an integer.
- getIntWithMax(Parameter, Parameter, int, int) - Method in class ec.util.ParameterDatabase
-
Searches down through databases to find a given parameter, whose value
must be an integer >= minValue and <= maxValue.
- getJobFilePrefix() - Method in class ec.display.ControlPanel
-
- getKeyFromNode(EvolutionState, int, GPNode, int) - Method in class ec.gp.ge.GESpecies
-
- getLabel() - Method in class ec.util.ParameterDatabase
-
Returns a String describing the location of the ParameterDatabase holding
this parameter, or "" if there is none.
- getLocalHost() - Static method in class ec.util.LocalHost
-
Returns an InetAddress
object encapsulating what is most
likely the machine's LAN IP address.
- getLocation(Parameter) - Method in class ec.util.ParameterDatabase
-
- getLocation(String) - Method in class ec.util.ParameterDatabase
-
- getLog(int) - Method in class ec.util.Output
-
Returns the given log.
- getLong(Parameter, Parameter) - Method in class ec.util.ParameterDatabase
-
Searches down through databases to find a given parameter, whose value
must be a long.
- getLong(Parameter, Parameter, long) - Method in class ec.util.ParameterDatabase
-
Searches down through databases to find a given parameter, whose value
must be a long >= minValue.
- getLong(Parameter, Parameter, long, long) - Method in class ec.util.ParameterDatabase
-
Deprecated.
- getLongWithDefault(Parameter, Parameter, long) - Method in class ec.util.ParameterDatabase
-
Searches down through databases to find a given parameter, which must be
a long.
- getLongWithMax(Parameter, Parameter, long, long) - Method in class ec.util.ParameterDatabase
-
Searches down through databases to find a given parameter, whose value
must be a long >= minValue and = < maxValue.
- getMatchingIndex() - Method in class ec.util.Lexer
-
Returns the index of the regular expression which matched the most recent token.
- getMatchingPosition() - Method in class ec.util.Lexer
-
Returns the position in the String just beyond the most recent token.
- getMatchingRule() - Method in class ec.util.Lexer
-
Returns the regular expression which matched the most recent token.
- getNextEvaluatedIndividual() - Method in class ec.eval.MasterProblem
-
This method blocks until an individual is available from the slaves (which will cause evaluatedIndividualAvailable()
to return true), at which time it returns the individual.
- getNextEvaluatedIndividual() - Method in class ec.steadystate.SteadyStateEvaluator
-
Returns an evaluated individual is in the queue and ready to come back to us.
- getNumArguments() - Method in class ec.gp.ge.GrammarFunctionNode
-
Returns the number of arguments.
- getNumChildren() - Method in class ec.util.ReflectedObject
-
- getNumChoices() - Method in class ec.gp.ge.GrammarRuleNode
-
Returns the current number of choices to the node.
- getNumFields() - Method in class ec.util.ReflectedObject
-
- getNumJobs() - Method in class ec.display.ControlPanel
-
- getNumObjectives() - Method in class ec.multiobjective.MultiObjectiveFitness
-
- getObjective(int) - Method in class ec.multiobjective.MultiObjectiveFitness
-
- getObjectives() - Method in class ec.multiobjective.MultiObjectiveFitness
-
Returns the objectives as an array.
- getOutstandingWorkers() - Method in class ec.util.ThreadPool
-
Returns the total number of outstanding workers (those working on something right now).
- getParameter() - Method in class ec.util.ParameterDatabaseEvent
-
- getPooledWorkers() - Method in class ec.util.ThreadPool
-
Returns the total number of pooled workers (those not working on something right now).
- getProbability(Object) - Method in class ec.BreedingSource
-
- getProbability(Object) - Method in interface ec.util.RandomChoiceChooser
-
Returns obj's probability
- getProbability(Object) - Method in interface ec.util.RandomChoiceChooserD
-
Returns obj's probability
- getProgram(EvolutionState, GPIndividual) - Method in class ec.gp.push.PushProblem
-
Produces a Push Program from the provided GP Individual's tree.
- getRandomIndividual(int, int, EvolutionState, int) - Method in class ec.multiobjective.spea2.SPEA2TournamentSelection
-
- getRandomIndividual(int, int, EvolutionState, int) - Method in class ec.select.TournamentSelection
-
Produces the index of a (typically uniformly distributed) randomly chosen individual
to fill the tournament.
- getRandomIndividual(int, int, EvolutionState, int) - Method in class ec.spatial.SpatialTournamentSelection
-
- getRankings(Individual[]) - Static method in class ec.multiobjective.MultiObjectiveFitness
-
Returns the Pareto rank for each individual.
- getRegexes() - Method in class ec.gp.ge.GrammarParser
-
Returns the regular expressions to use for tokenizing these rules.
- getResource(Parameter, Parameter) - Method in class ec.util.ParameterDatabase
-
Searches down through the databases to find a given parameter, whose
value must be an absolute or relative path name.
- getRoot() - Method in class ec.util.ReflectedObject
-
- gets_n_percent - Variable in class ec.select.GreedyOverselection
-
- getSeed(int, int) - Method in class ec.display.ControlPanel
-
- getShadowedValues(Parameter) - Method in class ec.util.ParameterDatabase
-
- getStore() - Method in class ec.util.Output
-
- getString(Parameter, Parameter) - Method in class ec.util.ParameterDatabase
-
Searches down through databases to find a given parameter.
- getStringWithDefault(Parameter, Parameter, String) - Method in class ec.util.ParameterDatabase
-
Searches down through databases to find a given parameter.
- getSubpopulationOfEvaluatedIndividual() - Method in class ec.steadystate.SteadyStateEvaluator
-
Returns the subpopulation of the last evaluated individual returned by getNextEvaluatedIndividual, or potentially -1 if
getNextEvaluatedIndividual was never called or hasn't returned an individual yet.
- getThreadCount(String) - Method in class ec.display.ControlPanel
-
- getThrowsErrors() - Method in class ec.util.Output
-
- getTotalWorkers() - Method in class ec.util.ThreadPool
-
Returns the total number of workers, both pooled and outstanding (working on something).
- getTournamentSizeToUse(MersenneTwisterFast) - Method in class ec.select.TournamentSelection
-
Returns a tournament size to use, at random, based on base size and probability of picking the size plus one.
- getType() - Method in class ec.util.ParameterDatabaseEvent
-
- getValue() - Method in class ec.display.ParameterValue
-
- getValue() - Method in class ec.util.ParameterDatabaseEvent
-
- getVerbosity() - Method in class ec.util.Output
-
- getVisibleLeaves() - Method in class ec.util.ParameterDatabaseTreeModel
-
- globalBest - Variable in class ec.pso.PSOBreeder
-
- globalBestFitness - Variable in class ec.pso.PSOBreeder
-
- globalCoeff - Variable in class ec.pso.PSOBreeder
-
- GP_PREAMBLE - Static variable in class ec.gp.ge.GEIndividual
-
- GPAtomicType - Class in ec.gp
-
A GPAtomicType is a simple, atomic GPType.
- GPAtomicType(String) - Constructor for class ec.gp.GPAtomicType
-
Use this constructor for GPAtomic Type unless you know what you're doing
- GPAtomicType() - Constructor for class ec.gp.GPAtomicType
-
Don't use this constructor unless you call setup(...) immediately after it.
- GPBreedDefaults - Class in ec.gp.breed
-
A static class that returns the base for "default values" which various
GP breeding
operators use, rather than making the user specify them all on a per-
species basis.
- GPBreedDefaults() - Constructor for class ec.gp.breed.GPBreedDefaults
-
- GPBreedingPipeline - Class in ec.gp
-
A GPBreedingPipeline is a BreedingPipeline which produces only
members of some subclass of GPSpecies.
- GPBreedingPipeline() - Constructor for class ec.gp.GPBreedingPipeline
-
- GPBuildDefaults - Class in ec.gp.build
-
- GPBuildDefaults() - Constructor for class ec.gp.build.GPBuildDefaults
-
- GPData - Class in ec.gp
-
GPData is the parent class of data transferred between GPNodes.
- GPData() - Constructor for class ec.gp.GPData
-
- GPDefaults - Class in ec.gp
-
A static class that returns the base for "default values" which GP-style
operators use, rather than making the user specify them all on a per-
species basis.
- GPDefaults() - Constructor for class ec.gp.GPDefaults
-
- GPFunctionSet - Class in ec.gp
-
GPFunctionSet is a Clique which represents a set of GPNode prototypes
forming a standard function set for forming certain trees in individuals.
- GPFunctionSet() - Constructor for class ec.gp.GPFunctionSet
-
- GPIndividual - Class in ec.gp
-
GPIndividual is an Individual used for GP evolution runs.
- GPIndividual() - Constructor for class ec.gp.GPIndividual
-
- GPInitializer - Class in ec.gp
-
GPInitializer is a SimpleInitializer which sets up all the Cliques,
( the initial
[tree/node]constraints, types, and function sets) for the GP system.
- GPInitializer() - Constructor for class ec.gp.GPInitializer
-
- GPKozaDefaults - Class in ec.gp.koza
-
A static class that returns the base for "default values" which Koza-style
operators use, rather than making the user specify them all on a per-
species basis.
- GPKozaDefaults() - Constructor for class ec.gp.koza.GPKozaDefaults
-
- GPNode - Class in ec.gp
-
GPNode is a GPNodeParent which is the abstract superclass of
all GP function nodes in trees.
- GPNode() - Constructor for class ec.gp.GPNode
-
- GPNodeBuilder - Class in ec.gp
-
GPNodeBuilder is a Prototype which defines the superclass for objects
which create ("grow") GP trees, whether for population initialization,
subtree mutation, or whatnot.
- GPNodeBuilder() - Constructor for class ec.gp.GPNodeBuilder
-
- GPNodeConstraints - Class in ec.gp
-
A GPNodeConstraints is a Clique which defines constraint information
common to many different GPNode functions, namely return types,
child types, and number of children.
- GPNodeConstraints() - Constructor for class ec.gp.GPNodeConstraints
-
- GPNodeGatherer - Class in ec.gp
-
GPNodeGatherer is a small container object for the GPNode.nodeInPosition(...)
method and GPNode.numNodes(...) method.
- GPNodeGatherer() - Constructor for class ec.gp.GPNodeGatherer
-
- GPNodeParent - Interface in ec.gp
-
GPNodeParent is a Prototype which identifies objects which may
be parents of GPNodes, namely: GPTrees and GPNodes.
- GPNODEPRINTTAB - Static variable in class ec.gp.GPNode
-
- GPNodeSelector - Interface in ec.gp
-
GPNodeSelector is a Prototype which describes algorithms which
select random nodes out of trees, typically marking them for
mutation, crossover, or whatnot.
- GPProblem - Class in ec.gp
-
A GPProblem is a Problem which is meant to efficiently handle GP
evaluation.
- GPProblem() - Constructor for class ec.gp.GPProblem
-
- GPSetType - Class in ec.gp
-
A GPSetType is a GPType which contains GPAtomicTypes in a set, and is used
as a generic GP type.
- GPSetType() - Constructor for class ec.gp.GPSetType
-
You should not construct new types.
- gpspecies - Variable in class ec.gp.ge.GESpecies
-
The GPSpecies subsidiary to GESpecies.
- GPSpecies - Class in ec.gp
-
GPSpecies is a simple individual which is suitable as a species
for GP subpopulations.
- GPSpecies() - Constructor for class ec.gp.GPSpecies
-
- GPTree - Class in ec.gp
-
GPTree is a GPNodeParent which holds the root GPNode of a tree
of GPNodes.
- GPTree() - Constructor for class ec.gp.GPTree
-
- GPTreeConstraints - Class in ec.gp
-
A GPTreeConstraints is a Clique which defines constraint information
common to many different GPTree trees, namely the tree type,
builder, and function set.
- GPTreeConstraints() - Constructor for class ec.gp.GPTreeConstraints
-
- GPType - Class in ec.gp
-
GPType is a Clique which represents types in
Strongly-Typed Genetic Programming (STGP).
- GPType() - Constructor for class ec.gp.GPType
-
- grammar - Variable in class ec.gp.ge.GESpecies
-
The parsed grammars.
- GrammarFunctionNode - Class in ec.gp.ge
-
A GrammarNode representing a GPNode in the GE Grammar.
- GrammarFunctionNode(GPFunctionSet, String) - Constructor for class ec.gp.ge.GrammarFunctionNode
-
Determines the GPNode from the function set by the name.
- GrammarFunctionNode(String) - Constructor for class ec.gp.ge.GrammarFunctionNode
-
- GrammarNode - Class in ec.gp.ge
-
The abstract superclass of nodes used by GrammarParser to construct a parse graph to generate
GEIndividuals.
- GrammarNode(String) - Constructor for class ec.gp.ge.GrammarNode
-
- grammarParser - Variable in class ec.gp.ge.GESpecies
-
Parser for each grammar -- khaled
- GrammarParser - Class in ec.gp.ge
-
A GrammarParser is the basic class for parsing a GE ruleset into a parse graph of GrammarNodes.
- GrammarParser() - Constructor for class ec.gp.ge.GrammarParser
-
- GrammarRuleNode - Class in ec.gp.ge
-
A GrammarNode representing a Rule in the GE Grammar.
- GrammarRuleNode(String) - Constructor for class ec.gp.ge.GrammarRuleNode
-
- GreedyOverselection - Class in ec.select
-
GreedyOverselection is a SelectionMethod which implements Koza-style
fitness-proportionate greedy overselection.
- GreedyOverselection() - Constructor for class ec.select.GreedyOverselection
-
- Group - Interface in ec
-
Groups are used for populations and subpopulations.
- GroupedProblemForm - Interface in ec.coevolve
-
GroupedProblemForm.java
- groupSize - Variable in class ec.coevolve.CompetitiveEvaluator
-
- GrowBuilder - Class in ec.gp.koza
-
GrowBuilder is a GPNodeBuilder which
implements the GROW tree building method described in Koza I/II.
- GrowBuilder() - Constructor for class ec.gp.koza.GrowBuilder
-
- growNode(EvolutionState, int, int, GPType, int, GPNodeParent, int, GPFunctionSet) - Method in class ec.gp.koza.KozaBuilder
-
A private function which recursively returns a GROW tree to newRootedTree(...)
- gt(Object, Object) - Method in interface ec.util.SortComparator
-
Returns true if a > b, else false
- gt(long, long) - Method in interface ec.util.SortComparatorL
-
Returns true if a > b, else false
- i_prototype - Variable in class ec.Species
-
The prototypical individual for this species.
- iAmServer - Variable in class ec.exchange.IslandExchange
-
whether the server should be running on the current island or not
- immigrantsSelectionMethod - Variable in class ec.exchange.IslandExchange
-
the selection method for immigrants
- includeSelf - Variable in class ec.pso.PSOBreeder
-
- ind - Variable in class ec.steadystate.QueueIndividual
-
- indices - Variable in class ec.gp.push.Terminal
-
For each PushInstruction, a pointer into instructions which gives the name of that instruction.
- indices - Variable in class ec.select.SUSSelection
-
An array of pointers to individuals in the population, shuffled along with the fitnesses array.
- Individual - Class in ec
-
An Individual is an item in the EC population stew which is evaluated
and assigned a fitness which determines its likelihood of selection.
- Individual() - Constructor for class ec.Individual
-
- INDIVIDUAL_INDEX_PREAMBLE - Static variable in class ec.Subpopulation
-
- IndividualPortrayal - Class in ec.display.portrayal
-
- individualReplaced(SteadyStateEvolutionState, int, int, int) - Method in class ec.BreedingPipeline
-
- individualReplaced(SteadyStateEvolutionState, int, int, int) - Method in class ec.parsimony.BucketTournamentSelection
-
- individualReplaced(SteadyStateEvolutionState, int, int, int) - Method in class ec.parsimony.DoubleTournamentSelection
-
- individualReplaced(SteadyStateEvolutionState, int, int, int) - Method in class ec.parsimony.RatioBucketTournamentSelection
-
- individualReplaced(SteadyStateEvolutionState, int, int, int) - Method in class ec.select.FirstSelection
-
- individualReplaced(SteadyStateEvolutionState, int, int, int) - Method in class ec.select.RandomSelection
-
- individualReplaced(SteadyStateEvolutionState, int, int, int) - Method in class ec.select.TournamentSelection
-
- individualReplaced(SteadyStateEvolutionState, int, int, int) - Method in class ec.steadystate.SteadyStateBreeder
-
Called whenever individuals have been replaced by new
individuals in the population.
- individualReplaced(SteadyStateEvolutionState, int, int, int) - Method in interface ec.steadystate.SteadyStateBSourceForm
-
Called whenever an individual has been replaced by another
in the population.
- individuals - Variable in class ec.Subpopulation
-
The subpopulation's individuals.
- individualsBredStatistics(SteadyStateEvolutionState, Individual[]) - Method in class ec.Statistics
-
STEADY-STATE: called each time new individuals are bred during the steady-state
process.
- individualsBredStatistics(SteadyStateEvolutionState, Individual[]) - Method in interface ec.steadystate.SteadyStateStatisticsForm
-
Called each time new individuals are bred during the steady-state
process.
- individualsEvaluatedStatistics(SteadyStateEvolutionState, Individual[], Individual[], int[], int[]) - Method in class ec.Statistics
-
STEADY-STATE: called each time new individuals are evaluated during the steady-state
process.
- individualsEvaluatedStatistics(SteadyStateEvolutionState, Individual[], Individual[], int[], int[]) - Method in interface ec.steadystate.SteadyStateStatisticsForm
-
Called each time new individuals are evaluated during the steady-state
process, NOT including the initial generation's individuals.
- INDS_PRODUCED - Static variable in class ec.breed.BufferedBreedingPipeline
-
- INDS_PRODUCED - Static variable in class ec.gp.breed.SizeFairCrossoverPipeline
-
- INDS_PRODUCED - Static variable in class ec.gp.koza.CrossoverPipeline
-
- INDS_PRODUCED - Static variable in class ec.gp.koza.MutationPipeline
-
- INDS_PRODUCED - Static variable in class ec.rule.breed.RuleCrossoverPipeline
-
- INDS_PRODUCED - Static variable in class ec.rule.breed.RuleMutationPipeline
-
- INDS_PRODUCED - Static variable in class ec.SelectionMethod
-
- indsToDieSelectionMethod - Variable in class ec.exchange.IslandExchange
-
the selection method for individuals to be replaced by immigrants
- informantCoeff - Variable in class ec.pso.PSOBreeder
-
- init - Variable in class ec.gp.GPTreeConstraints
-
The builder for the tree
- INITIAL_STACK_SIZE - Static variable in class ec.gp.ADFStack
-
- initialError(String) - Static method in class ec.util.Output
-
Prints an initial error to System.err.
- initialError(String, Parameter) - Static method in class ec.util.Output
-
Prints an initial error to System.err.
- initialError(String, Parameter, Parameter) - Static method in class ec.util.Output
-
Prints an initial error to System.err.
- InitializationPipeline - Class in ec.breed
-
InitializationPipeline is a BreedingPipeline which simply generates a new
random inidividual.
- InitializationPipeline() - Constructor for class ec.breed.InitializationPipeline
-
- initialize(ParameterDatabase, int) - Static method in class ec.Evolve
-
Initializes an evolutionary run given the parameters and a random seed adjustment (added to each random seed).
- initialize(ParameterDatabase, int, Output) - Static method in class ec.Evolve
-
Initializes an evolutionary run given the parameters and a random seed adjustment (added to each random seed),
with the Output pre-constructed.
- initializeContacts(EvolutionState) - Method in class ec.eval.MasterProblem
-
Initialize contacts with the slaves
- initializeContacts(EvolutionState) - Method in class ec.Evaluator
-
Called to set up remote evaluation network contacts when the run is started.
- initializeContacts(EvolutionState) - Method in class ec.exchange.InterPopulationExchange
-
Initializes contacts with other processes, if that's what you're doing.
- initializeContacts(EvolutionState) - Method in class ec.exchange.IslandExchange
-
Initializes contacts with other processes, if that's what you're doing.
- initializeContacts(EvolutionState) - Method in class ec.Exchanger
-
Initializes contacts with other processes, if that's what you're doing.
- initializeContacts(EvolutionState) - Method in class ec.gp.ge.GEProblem
-
- initializeContacts(EvolutionState) - Method in class ec.Problem
-
Called to set up remote evaluation network contacts when the run is started.
- initializeContacts(EvolutionState) - Method in class ec.simple.SimpleExchanger
-
Doesn't do anything.
- initializeGenomeSegmentsByEndIndices(EvolutionState, Parameter, Parameter, int) - Method in class ec.vector.VectorSpecies
-
Looks up genome segments using end indices.
- initializeGenomeSegmentsByStartIndices(EvolutionState, Parameter, Parameter, int) - Method in class ec.vector.VectorSpecies
-
Looks up genome segments using start indices.
- initializer - Variable in class ec.EvolutionState
-
The population initializer, a singleton object.
- Initializer - Class in ec
-
The Initializer is a singleton object whose job is to initialize the
population at the beginning of the run.
- Initializer() - Constructor for class ec.Initializer
-
- initialMessage(String) - Static method in class ec.util.Output
-
Prints an initial message to System.err.
- initialPopulation(EvolutionState, int) - Method in class ec.Initializer
-
Creates and returns a new initial population for the evolutionary run.
- initialPopulation(EvolutionState, int) - Method in class ec.simple.SimpleInitializer
-
Creates, populates, and returns a new population by making a new
population, calling setup(...) on it, and calling populate(...)
on it, assuming an unthreaded environment (thread 0).
- initialWarning(String) - Static method in class ec.util.Output
-
Prints an initial warning to System.err.
- initialWarning(String, Parameter) - Static method in class ec.util.Output
-
Prints an initial warning to System.err.
- initialWarning(String, Parameter, Parameter) - Static method in class ec.util.Output
-
Prints an initial warning to System.err.
- initScheme - Variable in class ec.gp.ge.GESpecies
-
- inNumericalTypeRange(double) - Method in class ec.vector.FloatVectorSpecies
-
- inNumericalTypeRange(double) - Method in class ec.vector.IntegerVectorSpecies
-
- inNumericalTypeRange(long) - Method in class ec.vector.IntegerVectorSpecies
-
- input - Variable in class ec.gp.GPProblem
-
The GPProblem's GPData
- input - Variable in class ec.util.DataPipe
-
The input stream
- inReserve - Variable in class ec.gp.ADFStack
-
- inssort(byte[]) - Static method in class ec.util.QuickSort
-
Insertion Sort
- inssort(short[]) - Static method in class ec.util.QuickSort
-
Insertion Sort
- inssort(char[]) - Static method in class ec.util.QuickSort
-
Insertion Sort
- inssort(int[]) - Static method in class ec.util.QuickSort
-
Insertion Sort
- inssort(long[]) - Static method in class ec.util.QuickSort
-
Insertion Sort
- inssort(float[]) - Static method in class ec.util.QuickSort
-
Insertion Sort
- inssort(double[]) - Static method in class ec.util.QuickSort
-
Insertion Sort
- inssort(Object[], SortComparator) - Static method in class ec.util.QuickSort
-
Insertion Sort
- inssort(long[], SortComparatorL) - Static method in class ec.util.QuickSort
-
Insertion Sort
- inssort(int[], SortComparatorL) - Static method in class ec.util.QuickSort
-
Insertion Sort
- instructions - Variable in class ec.gp.push.Terminal
-
Names of all the Push instructions I can be set to.
- INTEGER_ERC - Static variable in class ec.gp.push.Terminal
-
- IntegerVectorIndividual - Class in ec.vector
-
IntegerVectorIndividual is a VectorIndividual whose genome is an array of ints.
- IntegerVectorIndividual() - Constructor for class ec.vector.IntegerVectorIndividual
-
- IntegerVectorSpecies - Class in ec.vector
-
IntegerVectorSpecies is a subclass of VectorSpecies with special constraints
for integral vectors, namely ByteVectorIndividual, ShortVectorIndividual,
IntegerVectorIndividual, and LongVectorIndividual.
- IntegerVectorSpecies() - Constructor for class ec.vector.IntegerVectorSpecies
-
- InternalCrossoverPipeline - Class in ec.gp.breed
-
InternalCrossoverPipeline picks two subtrees from somewhere within an individual,
and crosses them over.
- InternalCrossoverPipeline() - Constructor for class ec.gp.breed.InternalCrossoverPipeline
-
- InterPopulationExchange - Class in ec.exchange
-
InterPopulationExchange is an Exchanger which implements a simple exchanger
between subpopulations.
- InterPopulationExchange() - Constructor for class ec.exchange.InterPopulationExchange
-
- interrupt() - Method in interface ec.util.ThreadPool.Worker
-
- intForNode(GPNode) - Method in class ec.gp.build.Uniform
-
- invsqrtC - Variable in class ec.eda.CMAESSpecies
-
C^{-1/2}.
- isFloatStackEmpty(Interpreter) - Method in class ec.gp.push.PushProblem
-
Tests to see if the interpreter's float stack is empty.
- isIdeal - Variable in class ec.simple.SimpleFitness
-
- isIdealFitness() - Method in class ec.Fitness
-
Should return true if this is a good enough fitness to end the run
- isIdealFitness() - Method in class ec.gp.koza.KozaFitness
-
- isIdealFitness() - Method in class ec.multiobjective.MultiObjectiveFitness
-
Returns true if this fitness is the "ideal" fitness.
- isIdealFitness() - Method in class ec.simple.SimpleFitness
-
- isIdealFitness(EvolutionState, Individual) - Method in class ec.steadystate.SteadyStateEvaluator
-
The SimpleEvaluator determines that a run is complete by asking
each individual in each population if he's optimal; if he
finds an individual somewhere that's optimal,
he signals that the run is complete.
- isInRange() - Method in class ec.vector.ByteVectorIndividual
-
Returns true if each gene value is within is specified [min,max] range.
- isInRange() - Method in class ec.vector.DoubleVectorIndividual
-
Returns true if each gene value is within is specified [min,max] range.
- isInRange() - Method in class ec.vector.FloatVectorIndividual
-
Returns true if each gene value is within is specified [min,max] range.
- isInRange() - Method in class ec.vector.IntegerVectorIndividual
-
Returns true if each gene value is within is specified [min,max] range.
- isInRange() - Method in class ec.vector.LongVectorIndividual
-
Returns true if each gene value is within is specified [min,max] range.
- isInRange() - Method in class ec.vector.ShortVectorIndividual
-
Returns true if each gene value is within is specified [min,max] range.
- isIntStackEmpty(Interpreter) - Method in class ec.gp.push.PushProblem
-
Tests to see if the interpreter's int stack is empty.
- IslandExchange - Class in ec.exchange
-
IslandExchange is an Exchanger which
implements a simple but quite functional asynchronous
island model for doing massive parallel distribution of evolution across
beowulf clusters.
- IslandExchange() - Constructor for class ec.exchange.IslandExchange
-
- isLeaf(Object) - Method in class ec.util.ReflectedObject
-
- isLoggingToSystemOut - Variable in class ec.util.Log
-
- isMaximizing() - Method in class ec.multiobjective.MultiObjectiveFitness
-
- isMaximizing(int) - Method in class ec.multiobjective.MultiObjectiveFitness
-
- isValidated(int[][], Object) - Method in class ec.vector.breed.ListCrossoverPipeline
-
A hook called by ListCrossoverPipeline to allow subclasses to further validate children crossover points.
- iterator(GPNodeGatherer) - Method in class ec.gp.GPNode
-
Returns an iterator over all the GPNodes in the subtree rooted by this GPNode,
filtered by the provided GPNodeGatherer.
- iterator(int) - Method in class ec.gp.GPNode
-
Returns an iterator over all the GPNodes in the subtree rooted by this GPNode,
filtered by the provided nodesearch option (either NODSEARCH_TERMINALS, NODESEARCH_NONTERMINALS,
or NODESEARCH_ALL)
- iterator() - Method in class ec.gp.GPNode
-
Returns an iterator over all the GPNodes in the subtree rooted by this GPNode.
- main(String[]) - Static method in class ec.display.Console
-
- main(String[]) - Static method in class ec.eval.Slave
-
- main(String[]) - Static method in class ec.Evolve
-
Top-level evolutionary loop.
- main(String[]) - Static method in class ec.exchange.IslandExchange
-
- main(String[]) - Static method in class ec.gp.ge.GrammarParser
-
A simple testing facility.
- main(String[]) - Static method in class ec.util.MersenneTwister
-
Tests the code.
- main(String[]) - Static method in class ec.util.MersenneTwisterFast
-
Tests the code.
- main(String[]) - Static method in class ec.util.ParameterDatabase
-
Test the ParameterDatabase
- main(String[]) - Static method in class ec.util.ThreadPool
-
- make(int, EvolutionState, int) - Method in class ec.parsimony.DoubleTournamentSelection
-
Produces the index of a person selected from among several by a tournament.
- makeBar(int, double[]) - Method in class ec.display.chart.BarChartStatistics
-
- makeChart() - Method in class ec.display.chart.BarChartStatistics
-
- makeChart() - Method in class ec.display.chart.ChartableStatistics
-
- makeChart() - Method in class ec.display.chart.XYSeriesChartStatistics
-
- makeCompressingInputStream(InputStream) - Static method in class ec.util.Output
-
Returns a compressing input stream using JZLib (http://www.jcraft.com/jzlib/).
- makeCompressingOutputStream(OutputStream) - Static method in class ec.util.Output
-
Returns a compressing output stream using JZLib (http://www.jcraft.com/jzlib/).
- makeCTree(boolean, boolean, boolean) - Method in class ec.gp.GPNode
-
Producess a String consisting of the tree in pseudo-C form, given that the parent already will wrap the
expression in parentheses (or not).
- makeGraphvizSubtree(String) - Method in class ec.gp.GPNode
-
Produces the inner code for a graphviz subtree.
- makeGraphvizTree() - Method in class ec.gp.GPNode
-
Produces the Graphviz code for a Graphviz tree of the subtree rooted at this node.
- makeLatexTree() - Method in class ec.gp.GPNode
-
Produces the LaTeX code for a LaTeX tree of the subtree rooted at this node, using the epic
and fancybox packages, as described in sections 10.5.2 (page 307)
and 10.1.3 (page 278) of The LaTeX Companion, respectively.
- makeLispTree(StringBuilder) - Method in class ec.gp.GPNode
-
Produces a tree for human consumption in Lisp form similar to that generated by printTreeForHumans().
- makeLispTree() - Method in class ec.gp.GPNode
-
- makeTree(EvolutionState, int[], GPTree, int, int, int, HashMap) - Method in class ec.gp.ge.GESpecies
-
makeTree, edits the tree that its given by adding a root (and all subtrees attached)
- makeTrees(EvolutionState, GEIndividual, GPTree[], int, HashMap) - Method in class ec.gp.ge.GESpecies
-
creates all of an individual's trees
- makeTrees(EvolutionState, int[], GPTree[], int, HashMap) - Method in class ec.gp.ge.GESpecies
-
- manhattanObjectiveDistance(MultiObjectiveFitness) - Method in class ec.multiobjective.MultiObjectiveFitness
-
Returns the Manhattan difference between two Fitnesses in Objective space.
- map(EvolutionState, double[], FloatVectorSpecies, int) - Method in class ec.eval.MetaProblem
-
- map(EvolutionState, GEIndividual, int, HashMap) - Method in class ec.gp.ge.GESpecies
-
Returns a dummy GPIndividual with a single tree which was built by mapping
over the elements of the given GEIndividual.
- MasterProblem - Class in ec.eval
-
MasterProblem.java
- MasterProblem() - Constructor for class ec.eval.MasterProblem
-
- masterproblem - Variable in class ec.Evaluator
-
- MAX_TRIES_BEFORE_WARNING - Static variable in class ec.eda.CMAESSpecies
-
- maxarity - Variable in class ec.gp.build.Uniform
-
- maxChildProduction() - Method in class ec.BreedingPipeline
-
Returns the maximum among the typicalIndsProduced() for any children --
a function that's useful internally, not very useful for you to call externally.
- maxCrossoverPercentage - Variable in class ec.vector.breed.ListCrossoverPipeline
-
- maxDepth - Variable in class ec.gp.breed.InternalCrossoverPipeline
-
The deepest tree the pipeline is allowed to form.
- maxDepth - Variable in class ec.gp.breed.SizeFairCrossoverPipeline
-
The deepest tree the pipeline is allowed to form.
- maxDepth - Variable in class ec.gp.build.PTC1
-
The largest maximum tree depth PTC1 can specify -- should be big.
- maxDepth - Variable in class ec.gp.build.PTC2
-
The largest maximum tree depth GROW can specify -- should be big.
- maxDepth - Variable in class ec.gp.koza.CrossoverPipeline
-
The deepest tree the pipeline is allowed to form.
- maxDepth - Variable in class ec.gp.koza.KozaBuilder
-
The largest maximum tree depth RAMPED HALF-AND-HALF can specify.
- maxFloatERC - Static variable in class ec.gp.push.Terminal
-
- maxGene - Variable in class ec.vector.FloatVectorSpecies
-
Max-gene value, per gene.
- maxGene(int) - Method in class ec.vector.FloatVectorSpecies
-
- maxGene - Variable in class ec.vector.IntegerVectorSpecies
-
Max-gene value, per gene.
- maxGene(int) - Method in class ec.vector.IntegerVectorSpecies
-
- maxGeneratable - Variable in class ec.breed.GenerationSwitchPipeline
-
- maxGeneratable - Variable in class ec.breed.MultiBreedingPipeline
-
- maximize - Variable in class ec.multiobjective.MultiObjectiveFitness
-
Maximization.
- MAXIMUM_INTEGER_IN_DOUBLE - Static variable in class ec.vector.DoubleVectorIndividual
-
- MAXIMUM_SHORT_IN_FLOAT - Static variable in class ec.vector.FloatVectorIndividual
-
- maximumMuLambdaDivisor() - Method in class ec.es.MuCommaLambdaBreeder
-
lambda should be no SMALLER than mu times this value.
- maximumMuLambdaDivisor() - Method in class ec.es.MuPlusLambdaBreeder
-
- maxInitialSize - Variable in class ec.vector.VectorSpecies
-
What's the largest legal genome?
- maxIntegerERC - Static variable in class ec.gp.push.Terminal
-
- maxObjective - Variable in class ec.multiobjective.MultiObjectiveFitness
-
Desired maximum fitness values.
- MAXPRINTBYTES - Static variable in class ec.gp.GPNode
-
- maxSize - Variable in class ec.gp.GPNodeBuilder
-
the minium possible size -- if unused, it's 0
- maxSize - Variable in class ec.gp.koza.CrossoverPipeline
-
The largest tree (measured as a nodecount) the pipeline is allowed to form.
- maxSize - Variable in class ec.gp.koza.MutationPipeline
-
The largest tree (measured as a nodecount) the pipeline is allowed to form.
- maxSize - Variable in class ec.rule.RuleSetConstraints
-
- maxtreesize - Variable in class ec.gp.build.Uniform
-
- merge(EvolutionState, Fitness) - Method in class ec.Fitness
-
Merges the other fitness into this fitness.
- merge(GrammarRuleNode) - Method in class ec.gp.ge.GrammarRuleNode
-
Adds to this node all the choices of another node.
- merge(EvolutionState, Individual) - Method in class ec.Individual
-
Replaces myself with the other Individual, while merging our evaluation results together.
- MERGE_BEST - Static variable in class ec.simple.SimpleEvaluator
-
- MERGE_MEAN - Static variable in class ec.simple.SimpleEvaluator
-
- MERGE_MEDIAN - Static variable in class ec.simple.SimpleEvaluator
-
- mergeForm - Variable in class ec.simple.SimpleEvaluator
-
- MersenneTwister - Class in ec.util
-
MersenneTwister and MersenneTwisterFast
- MersenneTwister() - Constructor for class ec.util.MersenneTwister
-
Constructor using the default seed.
- MersenneTwister(long) - Constructor for class ec.util.MersenneTwister
-
Constructor using a given seed.
- MersenneTwister(int[]) - Constructor for class ec.util.MersenneTwister
-
Constructor using an array of integers as seed.
- MersenneTwisterFast - Class in ec.util
-
MersenneTwister and MersenneTwisterFast
- MersenneTwisterFast() - Constructor for class ec.util.MersenneTwisterFast
-
Constructor using the default seed.
- MersenneTwisterFast(long) - Constructor for class ec.util.MersenneTwisterFast
-
Constructor using a given seed.
- MersenneTwisterFast(int[]) - Constructor for class ec.util.MersenneTwisterFast
-
Constructor using an array of integers as seed.
- message(String) - Method in class ec.util.Output
-
Posts a message.
- message() - Static method in class ec.util.Version
-
- MetaProblem - Class in ec.eval
-
MetaProblem is a special class for implenting so-called "Meta-Evolutionary Algorithms",
a topic related to "HyperHeuristics".
- MetaProblem() - Constructor for class ec.eval.MetaProblem
-
- MIN_QUEUE_SIZE - Static variable in class ec.gp.build.PTC2
-
- minChildProduction() - Method in class ec.BreedingPipeline
-
Returns the minimum among the typicalIndsProduced() for any children --
a function that's useful internally, not very useful for you to call externally.
- minChildSize - Variable in class ec.vector.breed.ListCrossoverPipeline
-
- minCrossoverPercentage - Variable in class ec.vector.breed.ListCrossoverPipeline
-
- minDepth - Variable in class ec.gp.koza.KozaBuilder
-
The smallest maximum tree depth RAMPED HALF-AND-HALF can specify.
- minFloatERC - Static variable in class ec.gp.push.Terminal
-
- minGene - Variable in class ec.vector.FloatVectorSpecies
-
Min-gene value, per gene.
- minGene(int) - Method in class ec.vector.FloatVectorSpecies
-
- minGene - Variable in class ec.vector.IntegerVectorSpecies
-
Min-gene value, per gene.
- minGene(int) - Method in class ec.vector.IntegerVectorSpecies
-
- minimumJavaVersion - Static variable in class ec.util.Version
-
- minimumSize - Variable in class ec.simple.SimpleBreeder
-
- minInitialSize - Variable in class ec.vector.VectorSpecies
-
What's the smallest legal genome?
- minIntegerERC - Static variable in class ec.gp.push.Terminal
-
- minObjective - Variable in class ec.multiobjective.MultiObjectiveFitness
-
Desired minimum fitness values.
- minSize - Variable in class ec.gp.GPNodeBuilder
-
- minSize - Variable in class ec.rule.RuleSetConstraints
-
- modifyParameters(EvolutionState, ParameterDatabase, int, Individual) - Method in class ec.eval.MetaProblem
-
Override this method to revise the provided parameter database to reflect the "parameters" specified in the
given meta-individual.
- modulo - Variable in class ec.exchange.IslandExchange
-
how often to send individuals
- modulus - Variable in class ec.simple.SimpleShortStatistics
-
- monitor - Variable in class ec.eval.MasterProblem
-
- moveFromSubstack(int) - Method in class ec.gp.ADFStack
-
Moves n items onto the stack (popss them off the substack and pushes them onto the stack).
- moveOntoSubstack(int) - Method in class ec.gp.ADFStack
-
Moves n items onto the substack (pops them off the stack and pushes them onto the substack).
- mu - Variable in class ec.eda.CMAESSpecies
-
The truncated individuals used to update the distribution.
- mu - Variable in class ec.es.MuCommaLambdaBreeder
-
- MuCommaLambdaBreeder - Class in ec.es
-
MuCommaLambdaBreeder is a Breeder which, together with
ESSelection, implements the (mu,lambda) breeding strategy and gathers
the comparison data you can use to implement a 1/5-rule mutation mechanism.
- MuCommaLambdaBreeder() - Constructor for class ec.es.MuCommaLambdaBreeder
-
- mueff - Variable in class ec.eda.CMAESSpecies
-
The "mu_{eff}" constant in CMA-ES.
- MULTI_FITNESS_POSTAMBLE - Static variable in class ec.multiobjective.MultiObjectiveFitness
-
- MultiBreedingPipeline - Class in ec.breed
-
MultiBreedingPipeline is a BreedingPipeline stores some n child sources;
each time it must produce an individual or two,
it picks one of these sources at random and has it do the production.
- MultiBreedingPipeline() - Constructor for class ec.breed.MultiBreedingPipeline
-
- MultiObjectiveDefaults - Class in ec.multiobjective
-
- MultiObjectiveDefaults() - Constructor for class ec.multiobjective.MultiObjectiveDefaults
-
- MultiObjectiveFitness - Class in ec.multiobjective
-
MultiObjectiveFitness is a subclass of Fitness which implements basic
multi-objective mechanisms suitable for being used with a variety of
multi-objective selection mechanisms, including ones using pareto-optimality.
- MultiObjectiveFitness() - Constructor for class ec.multiobjective.MultiObjectiveFitness
-
- MultiObjectiveStatistics - Class in ec.multiobjective
-
- MultiObjectiveStatistics() - Constructor for class ec.multiobjective.MultiObjectiveStatistics
-
- multipleBitVectorCrossover(int, int, int, int, Individual[], EvolutionState, int) - Method in class ec.vector.breed.MultipleVectorCrossoverPipeline
-
Crosses over the Bit Vector Individuals using a
uniform crossover method.
- multipleByteVectorCrossover(int, int, int, int, Individual[], EvolutionState, int) - Method in class ec.vector.breed.MultipleVectorCrossoverPipeline
-
Crosses over the Byte Vector Individuals using a
uniform crossover method.
- multipleDoubleVectorCrossover(int, int, int, int, Individual[], EvolutionState, int) - Method in class ec.vector.breed.MultipleVectorCrossoverPipeline
-
Crosses over the Double Vector Individuals using a
uniform crossover method.
- multipleFloatVectorCrossover(int, int, int, int, Individual[], EvolutionState, int) - Method in class ec.vector.breed.MultipleVectorCrossoverPipeline
-
Crosses over the Float Vector Individuals using a
uniform crossover method.
- multipleGeneVectorCrossover(int, int, int, int, Individual[], EvolutionState, int) - Method in class ec.vector.breed.MultipleVectorCrossoverPipeline
-
Crosses over the Gene Vector Individuals using a
uniform crossover method.
- multipleIntegerVectorCrossover(int, int, int, int, Individual[], EvolutionState, int) - Method in class ec.vector.breed.MultipleVectorCrossoverPipeline
-
Crosses over the Integer Vector Individuals using a uniform crossover method.
- multipleLongVectorCrossover(int, int, int, int, Individual[], EvolutionState, int) - Method in class ec.vector.breed.MultipleVectorCrossoverPipeline
-
Crosses over the Long Vector Individuals using a
uniform crossover method.
- multipleShortVectorCrossover(int, int, int, int, Individual[], EvolutionState, int) - Method in class ec.vector.breed.MultipleVectorCrossoverPipeline
-
Crosses over the Short Vector Individuals using a
uniform crossover method.
- MultipleVectorCrossoverPipeline - Class in ec.vector.breed
-
MultipleVectorCrossoverPipeline is a BreedingPipeline which implements a uniform
(any point) crossover between multiple vectors.
- MultipleVectorCrossoverPipeline() - Constructor for class ec.vector.breed.MultipleVectorCrossoverPipeline
-
- MultiPopCoevolutionaryEvaluator - Class in ec.coevolve
-
MultiPopCoevolutionaryEvaluator.java
- MultiPopCoevolutionaryEvaluator() - Constructor for class ec.coevolve.MultiPopCoevolutionaryEvaluator
-
- MultiSelection - Class in ec.select
-
MultiSelection is a SelectionMethod which stores some n subordinate
SelectionMethods.
- MultiSelection() - Constructor for class ec.select.MultiSelection
-
- MuPlusLambdaBreeder - Class in ec.es
-
MuPlusLambdaBreeder is a subclass of MuCommaLambdaBreeder which, together with
ESSelection, implements the (mu + lambda) breeding strategy and gathers
the comparison data you can use to implement a 1/5-rule mutation mechanism.
- MuPlusLambdaBreeder() - Constructor for class ec.es.MuPlusLambdaBreeder
-
- mustClone - Variable in class ec.breed.ReproductionPipeline
-
- mutate(EvolutionState, int) - Method in class ec.rule.Rule
-
Mutate the rule.
- mutate(EvolutionState, int) - Method in class ec.rule.RuleIndividual
-
Mutates the Individual.
- mutate(EvolutionState, int) - Method in class ec.rule.RuleSet
-
Mutates rules in the RuleSet independently with the given probability.
- mutate(EvolutionState, int) - Method in class ec.vector.Gene
-
Mutate the gene.
- MutateAllNodesPipeline - Class in ec.gp.breed
-
MutateAllNodesPipeline implements the AllNodes mutation algorithm described
in Kumar Chellapilla,
"A Preliminary Investigation into Evolving Modular Programs without Subtree
Crossover", GP98.
- MutateAllNodesPipeline() - Constructor for class ec.gp.breed.MutateAllNodesPipeline
-
- MutateDemotePipeline - Class in ec.gp.breed
-
MutateDemotePipeline works very similarly to the DemoteNode algorithm
described in Kumar Chellapilla,
"A Preliminary Investigation into Evolving Modular Programs without Subtree
Crossover", GP98, and is also similar to the "insertion" operator found in
Una-May O'Reilly's thesis,
"An Analysis of Genetic Programming".
- MutateDemotePipeline() - Constructor for class ec.gp.breed.MutateDemotePipeline
-
- mutateERC(EvolutionState, int) - Method in class ec.gp.ERC
-
Mutates the node's "value".
- MutateERCPipeline - Class in ec.gp.breed
-
MutateERCPipeline works very similarly to the "Gaussian" algorithm
described in Kumar Chellapilla,
"A Preliminary Investigation into Evolving Modular Programs without Subtree
Crossover", GP98.
- MutateERCPipeline() - Constructor for class ec.gp.breed.MutateERCPipeline
-
- mutateERCs(GPNode, EvolutionState, int) - Method in class ec.gp.breed.MutateERCPipeline
-
- MutateOneNodePipeline - Class in ec.gp.breed
-
MutateOneNodesPipeline implements the OneNode mutation algorithm described
in Kumar Chellapilla,
"A Preliminary Investigation into Evolving Modular Programs without Subtree
Crossover", GP98.
- MutateOneNodePipeline() - Constructor for class ec.gp.breed.MutateOneNodePipeline
-
- MutatePromotePipeline - Class in ec.gp.breed
-
MutatePromotePipeline works very similarly to the PromoteNode algorithm
described in Kumar Chellapilla,
"A Preliminary Investigation into Evolving Modular Programs without Subtree
Crossover", GP98, and is also similar to the "deletion" operator found in
Una-May O'Reilly's thesis,
"An Analysis of Genetic Programming".
- MutatePromotePipeline() - Constructor for class ec.gp.breed.MutatePromotePipeline
-
- MutateSwapPipeline - Class in ec.gp.breed
-
MutateSwapPipeline works very similarly to the Swap algorithm
described in Kumar Chellapilla,
"A Preliminary Investigation into Evolving Modular Programs without Subtree
Crossover", GP98.
- MutateSwapPipeline() - Constructor for class ec.gp.breed.MutateSwapPipeline
-
- mutationDistributionIndex - Variable in class ec.vector.FloatVectorSpecies
-
The distribution index for Polynomial Mutation, per gene.
- mutationDistributionIndex(int) - Method in class ec.vector.FloatVectorSpecies
-
- mutationIsBounded - Variable in class ec.vector.FloatVectorSpecies
-
Whether mutation is bounded to the min- and max-gene values, per gene.
- mutationIsBounded(int) - Method in class ec.vector.FloatVectorSpecies
-
- mutationIsBounded - Variable in class ec.vector.IntegerVectorSpecies
-
Whether mutation is bounded to the min- and max-gene values, per gene.
- mutationIsBounded(int) - Method in class ec.vector.IntegerVectorSpecies
-
- MutationPipeline - Class in ec.gp.koza
-
MutationPipeline is a GPBreedingPipeline which
implements a strongly-typed version of the
"Point Mutation" operator as described in Koza I.
- MutationPipeline() - Constructor for class ec.gp.koza.MutationPipeline
-
- mutationProbability - Variable in class ec.vector.VectorSpecies
-
Probability that a gene will mutate, per gene.
- mutationProbability(int) - Method in class ec.vector.VectorSpecies
-
- mutationType - Variable in class ec.vector.BitVectorSpecies
-
Mutation type, per gene.
- mutationType(int) - Method in class ec.vector.BitVectorSpecies
-
- mutationType - Variable in class ec.vector.FloatVectorSpecies
-
Mutation type, per gene.
- mutationType(int) - Method in class ec.vector.FloatVectorSpecies
-
- mutationType - Variable in class ec.vector.IntegerVectorSpecies
-
Mutation type, per gene.
- mutationType(int) - Method in class ec.vector.IntegerVectorSpecies
-
- mybase - Variable in class ec.BreedingPipeline
-
My parameter base -- I keep it around so I can print some messages that
are useful with it (not deep cloned)
- N_BUCKETS_DEFAULT - Static variable in class ec.parsimony.BucketTournamentSelection
-
Default number of buckets
- N_RULES - Static variable in class ec.rule.RuleSet
-
The message to appear when printing the rule set
- name - Variable in class ec.gp.ADF
-
The "function name" of the ADF, to distinguish it from other GP
functions you might provide.
- name() - Method in class ec.gp.ADF
-
- name - Variable in class ec.gp.ADFArgument
-
The "function name" of the ADFArgument, to distinguish it from other GP
functions you might provide.
- name() - Method in class ec.gp.ADFArgument
-
- name() - Method in class ec.gp.ERC
-
Returns the lowercase "name" of this ERC function class, some
simple, short name which distinguishes this class from other ERC
function classes you're using.
- name - Variable in class ec.gp.GPFunctionSet
-
Name of the GPFunctionSet
- name() - Method in class ec.gp.GPNode
-
Returns a Lisp-like atom for the node and any nodes of the same class.
- name - Variable in class ec.gp.GPNodeConstraints
-
The name of the GPNodeConstraints object -- this is NOT the
name of the GPNode
- name - Variable in class ec.gp.GPTreeConstraints
-
- name - Variable in class ec.gp.GPType
-
The name of the type
- name() - Method in class ec.gp.push.Terminal
-
- name - Variable in class ec.rule.RuleConstraints
-
The name of the RuleConstraints object
- name - Variable in class ec.rule.RuleSetConstraints
-
The name of the RuleSetConstraints object
- name - Static variable in class ec.util.Version
-
- neighborhood - Variable in class ec.pso.Particle
-
- neighborhood - Variable in class ec.pso.PSOBreeder
-
- neighborhoodBestFitness - Variable in class ec.pso.Particle
-
- neighborhoodBestGenome - Variable in class ec.pso.Particle
-
- neighborhoodSize - Variable in class ec.pso.PSOBreeder
-
- newIndividual(EvolutionState, int) - Method in class ec.eda.CMAESSpecies
-
- newIndividual(EvolutionState, int) - Method in class ec.gp.ge.GESpecies
-
This is an ugly hack to simulate the "Sensible Initialization",
First we create a GPIndividual, then reverse-map it to GEIndividuals,
We do not need to call IntegerVectorSpecies.newIndividual() since it is overriden
by the GPSpecies.newIndividual();
Moreover, as in the case for non-identical representations (i,e, GP-GE island
models etc,), the grammar rules, tree constraints, ERC's etc, are supposed to be
identical across all islands, so we are using the same "gpspecies" inside this class.
- newIndividual(EvolutionState, int) - Method in class ec.gp.GPSpecies
-
- newIndividual(EvolutionState, LineNumberReader) - Method in class ec.gp.GPSpecies
-
- newIndividual(EvolutionState, DataInput) - Method in class ec.gp.GPSpecies
-
- newIndividual(EvolutionState, int) - Method in class ec.rule.RuleSpecies
-
- newIndividual(EvolutionState, int) - Method in class ec.Species
-
Provides a brand-new individual to fill in a population.
- newIndividual(EvolutionState, LineNumberReader) - Method in class ec.Species
-
Provides an individual read from a stream, including
the fitness; the individual will
appear as it was written by printIndividual(...).
- newIndividual(EvolutionState, DataInput) - Method in class ec.Species
-
Provides an individual read from a DataInput source, including
the fitness.
- newIndividual(EvolutionState, int) - Method in class ec.vector.VectorSpecies
-
- newRootedTree(EvolutionState, GPType, int, GPNodeParent, GPFunctionSet, int, int) - Method in class ec.gp.build.PTC1
-
- newRootedTree(EvolutionState, GPType, int, GPNodeParent, GPFunctionSet, int, int) - Method in class ec.gp.build.PTC2
-
- newRootedTree(EvolutionState, GPType, int, GPNodeParent, GPFunctionSet, int, int) - Method in class ec.gp.build.RandomBranch
-
- newRootedTree(EvolutionState, GPType, int, GPNodeParent, GPFunctionSet, int, int) - Method in class ec.gp.build.RandTree
-
- newRootedTree(EvolutionState, GPType, int, GPNodeParent, GPFunctionSet, int, int) - Method in class ec.gp.build.Uniform
-
- newRootedTree(EvolutionState, GPType, int, GPNodeParent, GPFunctionSet, int, int) - Method in class ec.gp.GPNodeBuilder
-
- newRootedTree(EvolutionState, GPType, int, GPNodeParent, GPFunctionSet, int, int) - Method in class ec.gp.koza.FullBuilder
-
- newRootedTree(EvolutionState, GPType, int, GPNodeParent, GPFunctionSet, int, int) - Method in class ec.gp.koza.GrowBuilder
-
- newRootedTree(EvolutionState, GPType, int, GPNodeParent, GPFunctionSet, int, int) - Method in class ec.gp.koza.HalfBuilder
-
- newRootedTree(EvolutionState, GPType, int, GPNodeParent, GPFunctionSet, int, int) - Method in class ec.gp.push.PushBuilder
-
- next(int) - Method in class ec.util.MersenneTwister
-
Returns an integer with bits bits filled with a random number.
- nextBoolean() - Method in class ec.util.MersenneTwister
-
This method is missing from jdk 1.0.x and below.
- nextBoolean(float) - Method in class ec.util.MersenneTwister
-
This generates a coin flip with a probability probability
of returning true, else returning false.
- nextBoolean(double) - Method in class ec.util.MersenneTwister
-
This generates a coin flip with a probability probability
of returning true, else returning false.
- nextBoolean() - Method in class ec.util.MersenneTwisterFast
-
- nextBoolean(float) - Method in class ec.util.MersenneTwisterFast
-
This generates a coin flip with a probability probability
of returning true, else returning false.
- nextBoolean(double) - Method in class ec.util.MersenneTwisterFast
-
This generates a coin flip with a probability probability
of returning true, else returning false.
- nextByte() - Method in class ec.util.MersenneTwister
-
For completeness' sake, though it's not in java.util.Random.
- nextByte() - Method in class ec.util.MersenneTwisterFast
-
- nextBytes(byte[]) - Method in class ec.util.MersenneTwister
-
A bug fix for all versions of the JDK.
- nextBytes(byte[]) - Method in class ec.util.MersenneTwisterFast
-
- nextChar() - Method in class ec.util.MersenneTwister
-
For completeness' sake, though it's not in java.util.Random.
- nextChar() - Method in class ec.util.MersenneTwisterFast
-
- nextDouble() - Method in class ec.util.MersenneTwister
-
A bug fix for versions of JDK 1.1 and below.
- nextDouble(boolean, boolean) - Method in class ec.util.MersenneTwister
-
Returns a double in the range from 0.0 to 1.0, possibly inclusive of 0.0 and 1.0 themselves.
- nextDouble() - Method in class ec.util.MersenneTwisterFast
-
Returns a random double in the half-open range from [0.0,1.0).
- nextDouble(boolean, boolean) - Method in class ec.util.MersenneTwisterFast
-
Returns a double in the range from 0.0 to 1.0, possibly inclusive of 0.0 and 1.0 themselves.
- nextFloat() - Method in class ec.util.MersenneTwister
-
A bug fix for versions of JDK 1.1 and below.
- nextFloat(boolean, boolean) - Method in class ec.util.MersenneTwister
-
Returns a float in the range from 0.0f to 1.0f, possibly inclusive of 0.0f and 1.0f themselves.
- nextFloat() - Method in class ec.util.MersenneTwisterFast
-
Returns a random float in the half-open range from [0.0f,1.0f).
- nextFloat(boolean, boolean) - Method in class ec.util.MersenneTwisterFast
-
Returns a float in the range from 0.0f to 1.0f, possibly inclusive of 0.0f and 1.0f themselves.
- nextGaussian() - Method in class ec.util.MersenneTwister
-
A bug fix for all JDK code including 1.2.
- nextGaussian() - Method in class ec.util.MersenneTwisterFast
-
- nextInt(int) - Method in class ec.util.MersenneTwister
-
This method is missing from JDK 1.1 and below.
- nextInt() - Method in class ec.util.MersenneTwisterFast
-
- nextInt(int) - Method in class ec.util.MersenneTwisterFast
-
Returns an integer drawn uniformly from 0 to n-1.
- nextLong(long) - Method in class ec.util.MersenneTwister
-
This method is for completness' sake.
- nextLong() - Method in class ec.util.MersenneTwisterFast
-
Returns a long drawn uniformly from 0 to n-1.
- nextLong(long) - Method in class ec.util.MersenneTwisterFast
-
Returns a long drawn uniformly from 0 to n-1.
- nextShort() - Method in class ec.util.MersenneTwister
-
For completeness' sake, though it's not in java.util.Random.
- nextShort() - Method in class ec.util.MersenneTwisterFast
-
- nextToken(boolean) - Method in class ec.util.Lexer
-
Returns the next token as a string.
- nextToken() - Method in class ec.util.Lexer
-
Returns the next token as a string.
- NO_LOGS - Static variable in class ec.util.Output
-
When passed to print functions, doesn't do any printing
- NO_PROBABILITY - Static variable in class ec.BreedingSource
-
- NO_SIZE_LIMIT - Static variable in class ec.gp.koza.CrossoverPipeline
-
- NO_SIZE_LIMIT - Static variable in class ec.gp.koza.MutationPipeline
-
- NO_TREENUM - Static variable in class ec.gp.GPTree
-
- nodeConstraintRepository - Variable in class ec.gp.GPInitializer
-
- nodeConstraints - Variable in class ec.gp.GPInitializer
-
- nodeEquals(GPNode) - Method in class ec.gp.ADF
-
Determines node equality by comparing the class, associated tree, and
function name of the nodes.
- nodeEquals(GPNode) - Method in class ec.gp.ERC
-
Implement this to do ERC-to-ERC comparisons.
- nodeEquals(GPNode) - Method in class ec.gp.GPNode
-
Returns true if I am the "genetically" identical to this node, and our
children arrays are the same length, though
we may have different parents and children.
- nodeEquals(GPNode) - Method in class ec.gp.push.Terminal
-
- nodeEquivalentTo(GPNode) - Method in class ec.gp.GPNode
-
Returns true if I and the provided node are the same kind of
node -- that is, we could have both been cloned() and reset() from
the same prototype node.
- nodeHashCode() - Method in class ec.gp.ADF
-
Returns name.hashCode() + class.hashCode() + associatedTree.
- nodeHashCode() - Method in class ec.gp.ERC
-
Implement this to hash ERCs, along with other nodes, in such a way that two
"equal" ERCs will usually hash to the same value.
- nodeHashCode() - Method in class ec.gp.GPNode
-
Returns a hashcode usually associated with all nodes that are
equal to you (using nodeEquals(...)).
- nodeInPosition(int, GPNodeGatherer) - Method in class ec.gp.GPNode
-
Returns the p'th node, constrained by nodesearch,
in the subtree for which this GPNode is root.
- nodeInPosition(int, int) - Method in class ec.gp.GPNode
-
Returns the p'th node, constrained by nodesearch,
in the subtree for which this GPNode is root.
- nodes - Variable in class ec.gp.GPFunctionSet
-
The nodes that our GPTree can use: nodes[type][thenodes].
- nodes - Variable in class ec.gp.koza.KozaNodeSelector
-
The number of nodes in the tree, -1 if unknown.
- nodes_h - Variable in class ec.gp.GPFunctionSet
-
The nodes that our GPTree can use: arrays of nodes hashed by type.
- nodesByArity - Variable in class ec.gp.GPFunctionSet
-
Nodes == a given arity, that is: nodesByArity[type][arity][thenodes]
- nodesByName - Variable in class ec.gp.GPFunctionSet
-
The nodes that our GPTree can use, hashed by name().
- NODESEARCH_ALL - Static variable in class ec.gp.GPNode
-
- NODESEARCH_NONTERMINALS - Static variable in class ec.gp.GPNode
-
- NODESEARCH_TERMINALS - Static variable in class ec.gp.GPNode
-
- nodeselect - Variable in class ec.gp.breed.MutateAllNodesPipeline
-
How the pipeline chooses a subtree to mutate
- nodeselect - Variable in class ec.gp.breed.MutateERCPipeline
-
How the pipeline chooses a subtree to mutate
- nodeselect - Variable in class ec.gp.breed.MutateOneNodePipeline
-
How the pipeline chooses a subtree to mutate
- nodeselect - Variable in class ec.gp.koza.MutationPipeline
-
How the pipeline chooses a subtree to mutate
- nodeselect0 - Variable in class ec.gp.breed.InternalCrossoverPipeline
-
How the pipeline chooses the first subtree
- nodeselect1 - Variable in class ec.gp.breed.InternalCrossoverPipeline
-
How the pipeline chooses the second subtree
- nodeselect1 - Variable in class ec.gp.breed.SizeFairCrossoverPipeline
-
How the pipeline selects a node from individual 1
- nodeselect1 - Variable in class ec.gp.koza.CrossoverPipeline
-
How the pipeline selects a node from individual 1
- nodeselect2 - Variable in class ec.gp.breed.SizeFairCrossoverPipeline
-
How the pipeline selects a node from individual 2
- nodeselect2 - Variable in class ec.gp.koza.CrossoverPipeline
-
How the pipeline selects a node from individual 2
- Nonterminal - Class in ec.gp.push
-
ECJ implements Push's s-expressions as trees of nonterminals
and terminals.
- Nonterminal() - Constructor for class ec.gp.push.Nonterminal
-
- nonterminalProbabilities(int) - Method in class ec.gp.build.PTCFunctionSet
-
- nonterminalProbabilities(int) - Method in interface ec.gp.build.PTCFunctionSetForm
-
Returns an organized distribution (see ec.util.RandomChoice) of likelihoods
that various nonterminals in the function set will be chosen over other nonterminals
with the same return type.
- nonterminalProbability - Variable in class ec.gp.koza.KozaNodeSelector
-
The probability a nonterminal must be chosen.
- nonterminals - Variable in class ec.gp.GPFunctionSet
-
The nonterminals our GPTree can use: nonterminals[type][thenodes].
- nonterminals - Variable in class ec.gp.koza.KozaNodeSelector
-
The number of nonterminals in the tree, -1 if unknown.
- nonterminals_h - Variable in class ec.gp.GPFunctionSet
-
The nonterminals our GPTree can use: arrays of nonterminals hashed by type.
- nonterminalSelectionProbabilities(int) - Method in class ec.gp.build.PTCFunctionSet
-
- nonterminalSelectionProbabilities(int) - Method in interface ec.gp.build.PTCFunctionSetForm
-
Returns an array (by return type) of the probability that PTC1 must pick a
nonterminal over a terminal in order to guarantee the expectedTreeSize.
- nonterminalsOverArity - Variable in class ec.gp.GPFunctionSet
-
Nonterminals >= a given arity, that is: nonterminalsOverArity[type][arity][thenodes] --
this will be O(n^2).
- nonterminalsUnderArity - Variable in class ec.gp.GPFunctionSet
-
Nonterminals <= a given arity, that is: nonterminalsUnderArity[type][arity][thenodes] --
this will be O(n^2).
- NOSIZEGIVEN - Static variable in class ec.gp.GPNodeBuilder
-
Produces a new rooted tree of GPNodes whose root's return type is
swap-compatible with type.
- NOT_SET - Static variable in class ec.select.BestSelection
-
- NOT_SET - Static variable in class ec.simple.SimpleBreeder
-
- notifyMonitor(Object) - Method in class ec.eval.SlaveMonitor
-
- NSGA2_RANK_PREAMBLE - Static variable in class ec.multiobjective.nsga2.NSGA2MultiObjectiveFitness
-
- NSGA2_SPARSITY_PREAMBLE - Static variable in class ec.multiobjective.nsga2.NSGA2MultiObjectiveFitness
-
- NSGA2Breeder - Class in ec.multiobjective.nsga2
-
This SimpleBreeder subclass breeds a set of children from the Population, then
joins the original Population with the children in a (mu+mu) fashion.
- NSGA2Breeder() - Constructor for class ec.multiobjective.nsga2.NSGA2Breeder
-
- NSGA2Evaluator - Class in ec.multiobjective.nsga2
-
The NSGA2Evaluator is a simple generational evaluator which
evaluates every single member of the population (in a multithreaded fashion).
- NSGA2Evaluator() - Constructor for class ec.multiobjective.nsga2.NSGA2Evaluator
-
- NSGA2MultiObjectiveFitness - Class in ec.multiobjective.nsga2
-
NSGA2MultiObjectiveFitness is a subclass of MultiObjeciveFitness which
adds auxiliary fitness measures (sparsity, rank) largely used by MultiObjectiveStatistics.
- NSGA2MultiObjectiveFitness() - Constructor for class ec.multiobjective.nsga2.NSGA2MultiObjectiveFitness
-
- NUM_INDIVIDUALS_PREAMBLE - Static variable in class ec.Subpopulation
-
- NUM_SOURCES - Static variable in class ec.breed.BufferedBreedingPipeline
-
- NUM_SOURCES - Static variable in class ec.breed.CheckingPipeline
-
- NUM_SOURCES - Static variable in class ec.breed.GenerationSwitchPipeline
-
- NUM_SOURCES - Static variable in class ec.breed.InitializationPipeline
-
- NUM_SOURCES - Static variable in class ec.breed.ReproductionPipeline
-
- NUM_SOURCES - Static variable in class ec.breed.UniquePipeline
-
- NUM_SOURCES - Static variable in class ec.gp.breed.InternalCrossoverPipeline
-
- NUM_SOURCES - Static variable in class ec.gp.breed.MutateAllNodesPipeline
-
- NUM_SOURCES - Static variable in class ec.gp.breed.MutateDemotePipeline
-
- NUM_SOURCES - Static variable in class ec.gp.breed.MutateERCPipeline
-
- NUM_SOURCES - Static variable in class ec.gp.breed.MutateOneNodePipeline
-
- NUM_SOURCES - Static variable in class ec.gp.breed.MutatePromotePipeline
-
- NUM_SOURCES - Static variable in class ec.gp.breed.MutateSwapPipeline
-
- NUM_SOURCES - Static variable in class ec.gp.breed.RehangPipeline
-
- NUM_SOURCES - Static variable in class ec.gp.breed.SizeFairCrossoverPipeline
-
- NUM_SOURCES - Static variable in class ec.gp.koza.CrossoverPipeline
-
- NUM_SOURCES - Static variable in class ec.gp.koza.MutationPipeline
-
- NUM_SOURCES - Static variable in class ec.rule.breed.RuleCrossoverPipeline
-
- NUM_SOURCES - Static variable in class ec.rule.breed.RuleMutationPipeline
-
- NUM_SOURCES - Static variable in class ec.vector.breed.GeneDuplicationPipeline
-
- NUM_SOURCES - Static variable in class ec.vector.breed.ListCrossoverPipeline
-
- NUM_SOURCES - Static variable in class ec.vector.breed.VectorCrossoverPipeline
-
- NUM_SOURCES - Static variable in class ec.vector.breed.VectorMutationPipeline
-
- NUM_SUBPOPS_PREAMBLE - Static variable in class ec.Population
-
- numAtomicTypes - Variable in class ec.gp.GPInitializer
-
- numCharts - Variable in class ec.display.StatisticsChartPane
-
- NUMCHILDPERMUTATIONS - Variable in class ec.gp.build.Uniform
-
- numChildPermutations(GPInitializer, int, GPNode, int, int, int) - Method in class ec.gp.build.Uniform
-
- numCurrent - Variable in class ec.coevolve.MultiPopCoevolutionaryEvaluator
-
- numDuplicateRetries - Variable in class ec.breed.UniquePipeline
-
- numDuplicateRetries - Variable in class ec.Subpopulation
-
Do we allow duplicates?
- numElite - Variable in class ec.coevolve.MultiPopCoevolutionaryEvaluator
-
- numElites(EvolutionState, int) - Method in class ec.simple.SimpleBreeder
-
- NUMERIC_CONSTANT - Static variable in class ec.gp.ge.GrammarParser
-
- numEvaluations - Variable in class ec.EvolutionState
-
How many evaluations should we run for? If set to UNDEFINED (0), we run for the number of generations instead.
- numfuncnodes - Variable in class ec.gp.build.Uniform
-
- numGenerations - Variable in class ec.EvolutionState
-
The number of generations the evolutionary computation system will run until it ends.
- numInds - Variable in class ec.breed.ForceBreedingPipeline
-
- numLogs() - Method in class ec.util.Output
-
Returns the number of logs currently posted.
- numNodeConstraints - Variable in class ec.gp.GPInitializer
-
- numNodes(GPNodeGatherer) - Method in class ec.gp.GPNode
-
Returns the number of nodes, constrained by g.test(...)
in the subtree for which this GPNode is root.
- numNodes(int) - Method in class ec.gp.GPNode
-
Returns the number of nodes, constrained by nodesearch,
in the subtree for which this GPNode is root.
- numPrev - Variable in class ec.coevolve.MultiPopCoevolutionaryEvaluator
-
- numRead() - Method in class ec.util.DataPipe
-
Returns the number of elements read from the buffer so far (after the last reset()).
- numRuleConstraints - Variable in class ec.rule.RuleInitializer
-
- numRules - Variable in class ec.rule.RuleSet
-
How many rules are there used in the rules array
- numRules() - Method in class ec.rule.RuleSet
-
How many rules are there used in the rules array
- numRuleSetConstraints - Variable in class ec.rule.RuleInitializer
-
- numRulesForReset(RuleSet, EvolutionState, int) - Method in class ec.rule.RuleSetConstraints
-
Returns a stochastic value picked to specify the number of rules
to generate when calling reset() on this kind of Rule.
- numSetTypes - Variable in class ec.gp.GPInitializer
-
- numShuffled - Variable in class ec.coevolve.MultiPopCoevolutionaryEvaluator
-
- numSources() - Method in class ec.breed.BufferedBreedingPipeline
-
- numSources() - Method in class ec.breed.CheckingPipeline
-
- numSources() - Method in class ec.breed.ForceBreedingPipeline
-
- numSources() - Method in class ec.breed.GenerationSwitchPipeline
-
- numSources() - Method in class ec.breed.InitializationPipeline
-
- numSources() - Method in class ec.breed.MultiBreedingPipeline
-
- numSources() - Method in class ec.breed.ReproductionPipeline
-
- numSources() - Method in class ec.breed.UniquePipeline
-
- numSources() - Method in class ec.BreedingPipeline
-
Returns the number of sources to this pipeline.
- numSources() - Method in class ec.gp.breed.InternalCrossoverPipeline
-
- numSources() - Method in class ec.gp.breed.MutateAllNodesPipeline
-
- numSources() - Method in class ec.gp.breed.MutateDemotePipeline
-
- numSources() - Method in class ec.gp.breed.MutateERCPipeline
-
- numSources() - Method in class ec.gp.breed.MutateOneNodePipeline
-
- numSources() - Method in class ec.gp.breed.MutatePromotePipeline
-
- numSources() - Method in class ec.gp.breed.MutateSwapPipeline
-
- numSources() - Method in class ec.gp.breed.RehangPipeline
-
- numSources() - Method in class ec.gp.breed.SizeFairCrossoverPipeline
-
- numSources() - Method in class ec.gp.koza.CrossoverPipeline
-
- numSources() - Method in class ec.gp.koza.MutationPipeline
-
- numSources() - Method in class ec.rule.breed.RuleCrossoverPipeline
-
Returns 2
- numSources() - Method in class ec.rule.breed.RuleMutationPipeline
-
Returns 1
- numSources() - Method in class ec.vector.breed.GeneDuplicationPipeline
-
- numSources() - Method in class ec.vector.breed.ListCrossoverPipeline
-
- numSources() - Method in class ec.vector.breed.MultipleVectorCrossoverPipeline
-
Returns the number of parents
- numSources() - Method in class ec.vector.breed.VectorCrossoverPipeline
-
Returns 2
- numSources() - Method in class ec.vector.breed.VectorMutationPipeline
-
Returns 1
- numTests - Variable in class ec.simple.SimpleEvaluator
-
- numTreeConstraints - Variable in class ec.gp.GPInitializer
-
- NUMTREESOFTYPE - Variable in class ec.gp.build.Uniform
-
- numTreesOfType(GPInitializer, int, int, int) - Method in class ec.gp.build.Uniform
-
- NUMTREESROOTEDBYNODE - Variable in class ec.gp.build.Uniform
-
- numTreesRootedByNode(GPInitializer, int, GPNode, int) - Method in class ec.gp.build.Uniform
-
- numTries - Variable in class ec.gp.breed.InternalCrossoverPipeline
-
How many times the pipeline attempts to pick nodes until it gives up.
- numTries - Variable in class ec.gp.breed.SizeFairCrossoverPipeline
-
How many times the pipeline attempts to pick nodes until it gives up.
- numTries - Variable in class ec.gp.koza.CrossoverPipeline
-
How many times the pipeline attempts to pick nodes until it gives up.
- numTries - Variable in class ec.vector.breed.ListCrossoverPipeline
-
- numWritten() - Method in class ec.util.DataPipe
-
Returns the number of elements written to the buffer so far (after the last reset()).
- p_add - Variable in class ec.rule.RuleSetConstraints
-
- P_ADD_PROB - Static variable in class ec.rule.RuleSetConstraints
-
- P_ADF - Static variable in class ec.gp.ADF
-
- P_ADF - Static variable in class ec.gp.ADFStack
-
- P_ADFARGUMENT - Static variable in class ec.gp.ADFArgument
-
- P_ADFCONTEXT - Static variable in class ec.gp.ADFContext
-
- P_ADFSTACK - Static variable in class ec.gp.ADFStack
-
- P_ALTERNATIVE_GENERATOR - Static variable in class ec.eda.CMAESSpecies
-
- P_ALTERNATIVE_GENERATOR_TRIES - Static variable in class ec.eda.CMAESSpecies
-
- P_ALTERNATIVE_TERMINATION - Static variable in class ec.eda.CMAESSpecies
-
- P_ARGUMENT - Static variable in class ec.gp.ADFArgument
-
- P_ASSOCIATEDTREE - Static variable in class ec.gp.ADF
-
- P_ATOMIC - Static variable in class ec.gp.GPInitializer
-
- P_BEST - Static variable in class ec.select.BestSelection
-
Default base
- P_BITVECTORINDIVIDUAL - Static variable in class ec.vector.BitVectorIndividual
-
- P_BOLTZMANN - Static variable in class ec.select.BoltzmannSelection
-
Default base
- P_BREED - Static variable in class ec.breed.BreedDefaults
-
- P_BREED - Static variable in class ec.gp.breed.GPBreedDefaults
-
- P_BREEDER - Static variable in class ec.EvolutionState
-
- P_BREEDTHREADS - Static variable in class ec.Evolve
-
breedthreads parameter
- P_BUCKETS - Static variable in class ec.parsimony.BucketTournamentSelection
-
The number of buckets
- P_BUFFERED - Static variable in class ec.breed.BufferedBreedingPipeline
-
- P_BUFSIZE - Static variable in class ec.breed.BufferedBreedingPipeline
-
- P_BUILD - Static variable in class ec.gp.build.GPBuildDefaults
-
- P_BUILDER - Static variable in class ec.gp.koza.MutationPipeline
-
- P_BYTEVECTORINDIVIDUAL - Static variable in class ec.vector.ByteVectorIndividual
-
- P_C1 - Static variable in class ec.eda.CMAESSpecies
-
- P_CC - Static variable in class ec.eda.CMAESSpecies
-
- P_CHATTY - Static variable in class ec.exchange.InterPopulationExchange
-
Whether or not we're chatty
- P_CHATTY - Static variable in class ec.exchange.IslandExchange
-
Whether or not we're chatty
- P_CHECK - Static variable in class ec.breed.CheckingPipeline
-
- P_CHECKPOINT - Static variable in class ec.EvolutionState
-
- P_CHECKPOINTDIRECTORY - Static variable in class ec.EvolutionState
-
- P_CHECKPOINTMODULO - Static variable in class ec.EvolutionState
-
- P_CHECKPOINTPREFIX - Static variable in class ec.EvolutionState
-
- P_CHILD - Static variable in class ec.gp.GPNodeConstraints
-
- P_CHILD - Static variable in class ec.Statistics
-
- P_CHUNK_SIZE - Static variable in class ec.simple.SimpleEvaluator
-
- P_CHUNKSIZE - Static variable in class ec.vector.VectorSpecies
-
- P_CLIENT_PORT - Static variable in class ec.exchange.IslandExchange
-
The client port
- P_CLONE_PIPELINE_AND_POPULATION - Static variable in class ec.simple.SimpleBreeder
-
- P_CLONE_PROBLEM - Static variable in class ec.simple.SimpleEvaluator
-
- P_CMAES_SPECIES - Static variable in class ec.eda.CMAESSpecies
-
- P_CMU - Static variable in class ec.eda.CMAESSpecies
-
- P_COMPETE_STYLE - Static variable in class ec.coevolve.CompetitiveEvaluator
-
- P_COMPRESS - Static variable in class ec.simple.SimpleShortStatistics
-
- P_COMPRESS - Static variable in class ec.simple.SimpleStatistics
-
compress?
- P_COMPRESSED_COMMUNICATION - Static variable in class ec.exchange.IslandExchange
-
Whether the communication is compressed or not
- P_CONSTRAINTS - Static variable in class ec.rule.Rule
-
- P_CONSTRAINTS - Static variable in class ec.rule.RuleSet
-
The constraint for the rule set
- P_CONTEXT - Static variable in class ec.gp.ADFStack
-
- P_COOLING_RATE - Static variable in class ec.select.BoltzmannSelection
-
Cooling rate parameter
- P_COVARIANCE - Static variable in class ec.eda.CMAESSpecies
-
- P_Cr - Static variable in class ec.de.DEBreeder
-
- P_CROSSOVER - Static variable in class ec.gp.koza.CrossoverPipeline
-
- P_CROSSOVER - Static variable in class ec.rule.breed.RuleCrossoverPipeline
-
- P_CROSSOVER - Static variable in class ec.vector.breed.MultipleVectorCrossoverPipeline
-
default base
- P_CROSSOVER - Static variable in class ec.vector.breed.VectorCrossoverPipeline
-
- P_CROSSOVER_DISTRIBUTION_INDEX - Static variable in class ec.vector.VectorSpecies
-
- P_CROSSOVERPROB - Static variable in class ec.rule.breed.RuleCrossoverPipeline
-
- P_CROSSOVERPROB - Static variable in class ec.vector.VectorSpecies
-
- P_CROSSOVERTYPE - Static variable in class ec.vector.VectorSpecies
-
- P_CS - Static variable in class ec.eda.CMAESSpecies
-
- P_DAMPS - Static variable in class ec.eda.CMAESSpecies
-
- P_DATA - Static variable in class ec.gp.GPProblem
-
- p_database - Variable in class ec.eval.MetaProblem
-
A prototypical parameter database for the underlying (base-level) evolutionary computation system.
- P_DEBUG_INFO - Static variable in class ec.eval.MasterProblem
-
- P_DEFAULT_SUBPOP - Static variable in class ec.Population
-
- p_del - Variable in class ec.rule.RuleSetConstraints
-
- P_DEL_PROB - Static variable in class ec.rule.RuleSetConstraints
-
- P_DESELECTOR - Static variable in class ec.steadystate.SteadyStateBreeder
-
- P_DEST - Static variable in class ec.exchange.InterPopulationExchange
-
The prefix for destinations
- P_DEST_FOR_SUBPOP - Static variable in class ec.exchange.InterPopulationExchange
-
The number of destinations from current island
- P_DO_DEPTH - Static variable in class ec.gp.koza.KozaShortStatistics
-
- P_DO_DESCRIPTION - Static variable in class ec.simple.SimpleStatistics
-
- P_DO_FINAL - Static variable in class ec.simple.SimpleStatistics
-
- P_DO_GENERATION - Static variable in class ec.simple.SimpleStatistics
-
- P_DO_MESSAGE - Static variable in class ec.simple.SimpleStatistics
-
- P_DO_PER_GENERATION_DESCRIPTION - Static variable in class ec.simple.SimpleStatistics
-
- P_DO_SIZE - Static variable in class ec.simple.SimpleShortStatistics
-
- P_DO_SUBPOPS - Static variable in class ec.simple.SimpleShortStatistics
-
- P_DO_TIME - Static variable in class ec.simple.SimpleShortStatistics
-
- P_DOLENGTHFIRST - Static variable in class ec.parsimony.DoubleTournamentSelection
-
- P_DOUBLEVECTORINDIVIDUAL - Static variable in class ec.vector.DoubleVectorIndividual
-
- P_DUPLICATE_RETRIES - Static variable in class ec.vector.VectorSpecies
-
- P_DUPLICATION - Static variable in class ec.vector.breed.GeneDuplicationPipeline
-
- P_EC - Static variable in class ec.ECDefaults
-
- P_EDA - Static variable in class ec.eda.EDADefaults
-
- P_ELITE - Static variable in class ec.simple.SimpleBreeder
-
- P_ELITE_FRAC - Static variable in class ec.simple.SimpleBreeder
-
- P_EQUALSIZE - Static variable in class ec.gp.koza.MutationPipeline
-
- P_ES - Static variable in class ec.es.ESDefaults
-
- P_ESSELECT - Static variable in class ec.es.ESSelection
-
- P_EVALCOMPRESSION - Static variable in class ec.eval.Slave
-
- P_EVALCOMPRESSION - Static variable in class ec.eval.SlaveMonitor
-
- P_EVALMASTERHOST - Static variable in class ec.eval.Slave
-
- P_EVALMASTERPORT - Static variable in class ec.eval.Slave
-
- P_EVALMASTERPORT - Static variable in class ec.eval.SlaveMonitor
-
- P_EVALSLAVENAME - Static variable in class ec.eval.Slave
-
- P_EVALTHREADS - Static variable in class ec.Evolve
-
evalthreads parameter
- P_EVALUATIONS - Static variable in class ec.EvolutionState
-
- P_EVALUATOR - Static variable in class ec.EvolutionState
-
- P_EXCHANGER - Static variable in class ec.EvolutionState
-
- P_EXPECTED - Static variable in class ec.gp.build.PTC1
-
- P_EXTRA_BEHAVIOR - Static variable in class ec.Subpopulation
-
- P_F - Static variable in class ec.de.DEBreeder
-
- P_FILE - Static variable in class ec.eval.MetaProblem
-
- P_FILE - Static variable in class ec.gp.ge.GESpecies
-
- P_FILE - Static variable in class ec.Population
-
- P_FILE - Static variable in class ec.Subpopulation
-
- P_FINISHER - Static variable in class ec.EvolutionState
-
- P_FIRST - Static variable in class ec.select.FirstSelection
-
default base
- P_FITNESS - Static variable in class ec.Fitness
-
base parameter for defaults
- P_FITNESS - Static variable in class ec.Species
-
- P_FITNESSPROPORTIONATE - Static variable in class ec.select.FitProportionateSelection
-
Default base
- P_FLOAT - Static variable in class ec.gp.push.Terminal
-
- P_FloatVectorIndividual - Static variable in class ec.vector.FloatVectorIndividual
-
- P_FNOISE - Static variable in class ec.de.Best1BinDEBreeder
-
- P_FORCE - Static variable in class ec.breed.ForceBreedingPipeline
-
- P_FULL - Static variable in class ec.simple.SimpleShortStatistics
-
- P_FULLBUILDER - Static variable in class ec.gp.koza.FullBuilder
-
- P_FUNC - Static variable in class ec.gp.GPFunctionSet
-
- P_FUNC - Static variable in class ec.gp.push.Terminal
-
- P_FUNCTIONNAME - Static variable in class ec.gp.ADF
-
- P_FUNCTIONNAME - Static variable in class ec.gp.ADFArgument
-
- P_FUNCTIONSET - Static variable in class ec.gp.GPTreeConstraints
-
- P_FUNCTIONSETS - Static variable in class ec.gp.GPInitializer
-
- P_GE - Static variable in class ec.gp.ge.GEDefaults
-
- P_GEN_MAX - Static variable in class ec.breed.GenerationSwitchPipeline
-
- P_GEN_MAX - Static variable in class ec.breed.MultiBreedingPipeline
-
- P_GEN_MAX - Static variable in class ec.breed.UniquePipeline
-
- P_GENE - Static variable in class ec.vector.Gene
-
- P_GENE - Static variable in class ec.vector.GeneVectorSpecies
-
- P_GENERATIONS - Static variable in class ec.EvolutionState
-
- P_GENEVECTORINDIVIDUAL - Static variable in class ec.vector.GeneVectorIndividual
-
- P_GENOMESIZE - Static variable in class ec.vector.VectorSpecies
-
- P_GEOMETRIC_PROBABILITY - Static variable in class ec.vector.VectorSpecies
-
- P_GESPECIES - Static variable in class ec.gp.ge.GESpecies
-
- P_GETS - Static variable in class ec.select.GreedyOverselection
-
- P_GLOBAL_COEFFICIENT - Static variable in class ec.pso.PSOBreeder
-
- P_GP - Static variable in class ec.gp.GPDefaults
-
- P_GPDATA - Static variable in class ec.gp.GPData
-
- P_GPPROBLEM - Static variable in class ec.gp.GPProblem
-
- P_GPSPECIES - Static variable in class ec.gp.ge.GESpecies
-
- P_GPSPECIES - Static variable in class ec.gp.GPSpecies
-
- P_GREEDY - Static variable in class ec.select.GreedyOverselection
-
- P_GROUP_SIZE - Static variable in class ec.coevolve.CompetitiveEvaluator
-
- P_GROWBUILDER - Static variable in class ec.gp.koza.GrowBuilder
-
- P_HALFBUILDER - Static variable in class ec.gp.koza.HalfBuilder
-
- P_HOMOLOGOUS - Static variable in class ec.gp.breed.SizeFairCrossoverPipeline
-
- P_IAMSLAVE - Static variable in class ec.Evaluator
-
- P_INCLUDE_SELF - Static variable in class ec.pso.PSOBreeder
-
- P_IND_COMPETES - Static variable in class ec.spatial.SpatialTournamentSelection
-
Some models assume an individual is always selected to compete for breeding a child that would
take its location in space.
- P_INDIVIDUAL - Static variable in class ec.Individual
-
A reasonable parameter base element for individuals
- P_INDIVIDUAL - Static variable in class ec.Species
-
- P_INFORMANT_COEFFICIENT - Static variable in class ec.pso.PSOBreeder
-
- P_INIT - Static variable in class ec.breed.InitializationPipeline
-
- P_INIT - Static variable in class ec.gp.GPTreeConstraints
-
- P_INITIALIZER - Static variable in class ec.EvolutionState
-
- P_INITSCHEME - Static variable in class ec.gp.ge.GESpecies
-
- P_INSTRUCTION - Static variable in class ec.gp.push.PushInstruction
-
- P_INSTRUCTION - Static variable in class ec.gp.push.Terminal
-
- P_INTEGER - Static variable in class ec.gp.push.Terminal
-
- P_INTEGERVECTORINDIVIDUAL - Static variable in class ec.vector.IntegerVectorIndividual
-
- P_INTERNALCROSSOVER - Static variable in class ec.gp.breed.InternalCrossoverPipeline
-
- P_IS_SERVER - Static variable in class ec.exchange.IslandExchange
-
Whether the server is also on this island
- P_JOB_SIZE - Static variable in class ec.eval.MasterProblem
-
- P_KILL_PROPORTION - Static variable in class ec.parsimony.TarpeianStatistics
-
one in n individuals are killed
- P_KOZA - Static variable in class ec.gp.koza.GPKozaDefaults
-
- P_KOZAFITNESS - Static variable in class ec.gp.koza.KozaFitness
-
- P_LAMBDA - Static variable in class ec.eda.CMAESSpecies
-
- P_LAMBDA - Static variable in class ec.es.MuCommaLambdaBreeder
-
- P_LIKELIHOOD - Static variable in class ec.BreedingPipeline
-
Indicates the probability that the Breeding Pipeline will perform its mutative action instead of just doing reproduction.
- P_LINEDISTANCE - Static variable in class ec.vector.VectorSpecies
-
- P_LIST_CROSSOVER - Static variable in class ec.vector.breed.ListCrossoverPipeline
-
- P_LONGVECTORINDIVIDUAL - Static variable in class ec.vector.LongVectorIndividual
-
- P_MASTERPROBLEM - Static variable in class ec.Evaluator
-
- P_MAX - Static variable in class ec.gp.push.Terminal
-
- P_MAX_CROSSOVER_PERCENT - Static variable in class ec.vector.breed.ListCrossoverPipeline
-
- P_MAXDEPTH - Static variable in class ec.gp.breed.InternalCrossoverPipeline
-
- P_MAXDEPTH - Static variable in class ec.gp.breed.MutateDemotePipeline
-
- P_MAXDEPTH - Static variable in class ec.gp.breed.SizeFairCrossoverPipeline
-
- P_MAXDEPTH - Static variable in class ec.gp.build.PTC1
-
- P_MAXDEPTH - Static variable in class ec.gp.build.PTC2
-
- P_MAXDEPTH - Static variable in class ec.gp.koza.CrossoverPipeline
-
- P_MAXDEPTH - Static variable in class ec.gp.koza.KozaBuilder
-
- P_MAXDEPTH - Static variable in class ec.gp.koza.MutationPipeline
-
- P_MAXGENE - Static variable in class ec.vector.FloatVectorSpecies
-
- P_MAXGENE - Static variable in class ec.vector.IntegerVectorSpecies
-
- P_MAXIMIZE - Static variable in class ec.multiobjective.MultiObjectiveFitness
-
Is higher better?
- P_MAXIMUMNUMBEROFCONCURRENTJOBSPERSLAVE - Static variable in class ec.eval.SlaveMonitor
-
- P_MAXOBJECTIVES - Static variable in class ec.multiobjective.MultiObjectiveFitness
-
parameter for max fitness values
- P_MAXSIZE - Static variable in class ec.gp.GPNodeBuilder
-
- P_MAXSIZE - Static variable in class ec.gp.koza.CrossoverPipeline
-
- P_MAXSIZE - Static variable in class ec.gp.koza.MutationPipeline
-
- P_MAXSIZE - Static variable in class ec.rule.RuleSetConstraints
-
- P_MEAN - Static variable in class ec.eda.CMAESSpecies
-
- P_MEMBER - Static variable in class ec.gp.GPSetType
-
- P_MERGE - Static variable in class ec.simple.SimpleEvaluator
-
- P_MIN - Static variable in class ec.gp.push.Terminal
-
- P_MIN_CHILD_SIZE - Static variable in class ec.vector.breed.ListCrossoverPipeline
-
- P_MIN_CROSSOVER_PERCENT - Static variable in class ec.vector.breed.ListCrossoverPipeline
-
- P_MINDEPTH - Static variable in class ec.gp.koza.KozaBuilder
-
- P_MINGENE - Static variable in class ec.vector.FloatVectorSpecies
-
- P_MINGENE - Static variable in class ec.vector.IntegerVectorSpecies
-
- P_MINIMUM_SIZE - Static variable in class ec.simple.SimpleBreeder
-
- P_MINOBJECTIVES - Static variable in class ec.multiobjective.MultiObjectiveFitness
-
parameter for min fitness values
- P_MINSIZE - Static variable in class ec.gp.GPNodeBuilder
-
- P_MINSIZE - Static variable in class ec.rule.RuleSetConstraints
-
- P_MODULO - Static variable in class ec.exchange.InterPopulationExchange
-
The parameter for the modulo (how many generations should pass between consecutive sendings of individuals
- P_MU - Static variable in class ec.eda.CMAESSpecies
-
- P_MU - Static variable in class ec.es.MuCommaLambdaBreeder
-
- P_MU_FRACTION - Static variable in class ec.es.MuCommaLambdaBreeder
-
- P_MULTI - Static variable in class ec.multiobjective.MultiObjectiveDefaults
-
- P_MULTIBREED - Static variable in class ec.breed.GenerationSwitchPipeline
-
- P_MULTIBREED - Static variable in class ec.breed.MultiBreedingPipeline
-
- P_MULTISELECT - Static variable in class ec.select.MultiSelection
-
- P_MUSTCLONE - Static variable in class ec.breed.ReproductionPipeline
-
- P_MUTATEALLNODES - Static variable in class ec.gp.breed.MutateAllNodesPipeline
-
- P_MUTATEDEMOTE - Static variable in class ec.gp.breed.MutateDemotePipeline
-
- P_MUTATEERC - Static variable in class ec.gp.breed.MutateERCPipeline
-
- P_MUTATEONENODE - Static variable in class ec.gp.breed.MutateOneNodePipeline
-
- P_MUTATEPROMOTE - Static variable in class ec.gp.breed.MutatePromotePipeline
-
- P_MUTATESWAP - Static variable in class ec.gp.breed.MutateSwapPipeline
-
- P_MUTATION - Static variable in class ec.gp.koza.MutationPipeline
-
- P_MUTATION - Static variable in class ec.rule.breed.RuleMutationPipeline
-
- P_MUTATION - Static variable in class ec.vector.breed.VectorMutationPipeline
-
- P_MUTATION_BOUNDED - Static variable in class ec.vector.FloatVectorSpecies
-
- P_MUTATION_BOUNDED - Static variable in class ec.vector.IntegerVectorSpecies
-
- P_MUTATION_DISTRIBUTION_INDEX - Static variable in class ec.vector.FloatVectorSpecies
-
- P_MUTATIONPROB - Static variable in class ec.vector.VectorSpecies
-
- P_MUTATIONTYPE - Static variable in class ec.vector.BitVectorSpecies
-
- P_MUTATIONTYPE - Static variable in class ec.vector.FloatVectorSpecies
-
- P_MUTATIONTYPE - Static variable in class ec.vector.IntegerVectorSpecies
-
- P_MUZZLE - Static variable in class ec.eval.MetaProblem
-
- P_MUZZLE - Static variable in class ec.eval.Slave
-
- P_MUZZLE - Static variable in class ec.Statistics
-
- P_N - Static variable in class ec.select.BestSelection
-
- P_N_FRACTION - Static variable in class ec.select.BestSelection
-
- P_N_SIZE - Static variable in class ec.spatial.SpatialTournamentSelection
-
The size of the neighborhood from where parents are selected.
- P_NAME - Static variable in class ec.gp.GPFunctionSet
-
- P_NAME - Static variable in class ec.gp.GPNodeConstraints
-
- P_NAME - Static variable in class ec.gp.GPTreeConstraints
-
- P_NAME - Static variable in class ec.gp.GPType
-
- P_NAME - Static variable in class ec.rule.RuleConstraints
-
- P_NAME - Static variable in class ec.rule.RuleSetConstraints
-
The size of a byte
- P_NEIGHBORHOOD - Static variable in class ec.pso.PSOBreeder
-
- P_NEIGHBORHOOD_SIZE - Static variable in class ec.pso.PSOBreeder
-
- P_NODE - Static variable in class ec.gp.GPNode
-
- P_NODECONSTRAINTS - Static variable in class ec.gp.GPInitializer
-
- P_NODECONSTRAINTS - Static variable in class ec.gp.GPNode
-
- P_NODESELECTOR - Static variable in class ec.gp.GPBreedingPipeline
-
Standard parameter for node-selectors associated with a GPBreedingPipeline
- P_NODESELECTOR - Static variable in class ec.gp.koza.KozaNodeSelector
-
- P_NONTERMINAL_PROBABILITY - Static variable in class ec.gp.koza.KozaNodeSelector
-
- P_NUM_ELITE - Static variable in class ec.coevolve.MultiPopCoevolutionaryEvaluator
-
- P_NUM_IND - Static variable in class ec.coevolve.MultiPopCoevolutionaryEvaluator
-
- P_NUM_INSTRUCTIONS - Static variable in class ec.gp.push.Terminal
-
- P_NUM_PARAMS - Static variable in class ec.eval.MetaProblem
-
- P_NUM_RAND_IND - Static variable in class ec.coevolve.MultiPopCoevolutionaryEvaluator
-
- P_NUM_SEGMENTS - Static variable in class ec.vector.IntegerVectorSpecies
-
- P_NUM_SEGMENTS - Static variable in class ec.vector.VectorSpecies
-
- P_NUM_SHUFFLED - Static variable in class ec.coevolve.MultiPopCoevolutionaryEvaluator
-
- P_NUM_TESTS - Static variable in class ec.simple.SimpleEvaluator
-
- P_NUM_TRIES - Static variable in class ec.gp.breed.InternalCrossoverPipeline
-
- P_NUM_TRIES - Static variable in class ec.gp.breed.MutateDemotePipeline
-
- P_NUM_TRIES - Static variable in class ec.gp.breed.MutatePromotePipeline
-
- P_NUM_TRIES - Static variable in class ec.gp.breed.MutateSwapPipeline
-
- P_NUM_TRIES - Static variable in class ec.gp.breed.RehangPipeline
-
- P_NUM_TRIES - Static variable in class ec.gp.breed.SizeFairCrossoverPipeline
-
- P_NUM_TRIES - Static variable in class ec.gp.koza.CrossoverPipeline
-
- P_NUM_TRIES - Static variable in class ec.gp.koza.MutationPipeline
-
- P_NUM_TRIES - Static variable in class ec.vector.breed.ListCrossoverPipeline
-
- P_NUM_VALS - Static variable in class ec.eval.MetaProblem
-
- P_NUMCHILDREN - Static variable in class ec.Statistics
-
- P_NUMINDS - Static variable in class ec.breed.ForceBreedingPipeline
-
- P_NUMOBJECTIVES - Static variable in class ec.multiobjective.MultiObjectiveFitness
-
parameter for size of objectives
- P_NUMRULESETS - Static variable in class ec.rule.RuleIndividual
-
- P_NUMSELECTS - Static variable in class ec.select.MultiSelection
-
- P_NUMSIZES - Static variable in class ec.gp.GPNodeBuilder
-
- P_NUMSIZES - Static variable in class ec.rule.RuleSetConstraints
-
- P_NUMSOURCES - Static variable in class ec.BreedingPipeline
-
Standard parameter for number of sources (only used if numSources
returns DYNAMIC_SOURCES
- P_NUMTIMES - Static variable in class ec.breed.CheckingPipeline
-
- P_NUMTREES - Static variable in class ec.gp.GPIndividual
-
- P_OFFSET - Static variable in class ec.exchange.InterPopulationExchange
-
How many generations to pass at the beginning of the evolution before the first
emigration from the current subpopulation
- P_ONESHOT - Static variable in class ec.eval.Slave
-
Should slave go into an infinite loop looking for new masters after the master has quit, or not?
- P_OUT_OF_BOUNDS_RETRIES - Static variable in class ec.de.DEBreeder
-
- P_OUTOFBOUNDS_RETRIES - Static variable in class ec.vector.FloatVectorSpecies
-
- P_OVER_EVAL - Static variable in class ec.coevolve.CompetitiveEvaluator
-
- P_OWN_ID - Static variable in class ec.exchange.IslandExchange
-
The id of the island
- P_PARAM - Static variable in class ec.eval.MetaProblem
-
- P_PARETO_FRONT_FILE - Static variable in class ec.multiobjective.MultiObjectiveStatistics
-
front file parameter
- P_PARSER - Static variable in class ec.gp.ge.GESpecies
-
- P_PARSER - Static variable in class ec.gp.ge.GrammarParser
-
- P_PASSES - Static variable in class ec.gp.ge.GESpecies
-
- P_PERSONAL_COEFFICIENT - Static variable in class ec.pso.PSOBreeder
-
- P_PF - Static variable in class ec.de.Rand1EitherOrDEBreeder
-
- P_PICKGROWPROBABILITY - Static variable in class ec.gp.koza.HalfBuilder
-
- P_PICKWORST - Static variable in class ec.parsimony.BucketTournamentSelection
-
If the worst individual should be picked in the tournament
- P_PICKWORST - Static variable in class ec.parsimony.DoubleTournamentSelection
-
- P_PICKWORST - Static variable in class ec.parsimony.RatioBucketTournamentSelection
-
if the worst individual should be picked in the tournament
- P_PICKWORST - Static variable in class ec.select.BestSelection
-
- P_PICKWORST - Static variable in class ec.select.TournamentSelection
-
- P_PICKWORST2 - Static variable in class ec.parsimony.DoubleTournamentSelection
-
- P_PIPE - Static variable in class ec.Species
-
- P_POLYNOMIAL_ALTERNATIVE - Static variable in class ec.vector.FloatVectorSpecies
-
- P_POP - Static variable in class ec.Initializer
-
parameter for a new population
- P_PRINT_STYLE - Static variable in class ec.gp.GPTree
-
- P_PRINTACCESSEDPARAMETERS - Static variable in class ec.Evolve
-
- P_PRINTALLPARAMETERS - Static variable in class ec.Evolve
-
- P_PRINTUNACCESSEDPARAMETERS - Static variable in class ec.Evolve
-
- P_PRINTUNUSEDPARAMETERS - Static variable in class ec.Evolve
-
- P_PRINTUSEDPARAMETERS - Static variable in class ec.Evolve
-
- P_PROB - Static variable in class ec.BreedingSource
-
- P_PROBABILITY - Static variable in class ec.gp.GPNodeConstraints
-
- P_PROBABILITY - Static variable in class ec.parsimony.ProportionalTournamentSelection
-
The parameter for the probability of having the tournament based on fitness
- P_PROBLEM - Static variable in class ec.Evaluator
-
- p_problem - Variable in class ec.Evaluator
-
- P_PROBLEM - Static variable in class ec.gp.ge.GEProblem
-
- P_PROBLEM - Static variable in class ec.Problem
-
- P_PROPORTIONAL_TOURNAMENT - Static variable in class ec.parsimony.ProportionalTournamentSelection
-
default base
- P_PTC1 - Static variable in class ec.gp.build.PTC1
-
- P_PTC2 - Static variable in class ec.gp.build.PTC2
-
- P_PUSH - Static variable in class ec.gp.push.PushDefaults
-
- P_PUSHBUILDER - Static variable in class ec.gp.push.PushBuilder
-
- P_QUITONRUNCOMPLETE - Static variable in class ec.EvolutionState
-
- P_RAND_ORDER_PROB - Static variable in class ec.rule.RuleSetConstraints
-
- P_RANDOM - Static variable in class ec.select.RandomSelection
-
default base
- P_RANDOM_WALK_PROBABILITY - Static variable in class ec.vector.FloatVectorSpecies
-
- P_RANDOM_WALK_PROBABILITY - Static variable in class ec.vector.IntegerVectorSpecies
-
- P_RANDOMBRANCH - Static variable in class ec.gp.build.RandomBranch
-
- P_RANDOMBRANCH - Static variable in class ec.gp.build.RandTree
-
- p_randorder - Variable in class ec.rule.RuleSetConstraints
-
- P_RATIO - Static variable in class ec.parsimony.RatioBucketTournamentSelection
-
The value of RATIO: each step, the worse 1/RATIO individuals are assigned the same fitness
- P_RATIO_BUCKET_TOURNAMENT - Static variable in class ec.parsimony.RatioBucketTournamentSelection
-
default base
- P_REDUCE_BY - Static variable in class ec.simple.SimpleBreeder
-
- P_REEVALUATE_ELITES - Static variable in class ec.simple.SimpleBreeder
-
- P_REEVALUATE_INDIVIDUALS - Static variable in class ec.eval.MetaProblem
-
- P_REHANG - Static variable in class ec.gp.breed.RehangPipeline
-
- P_REPLACEMENT_PROBABILITY - Static variable in class ec.steadystate.SteadyStateEvolutionState
-
- P_REPRODUCE - Static variable in class ec.breed.ReproductionPipeline
-
- P_RESCHEDULELOSTJOBS - Static variable in class ec.eval.SlaveMonitor
-
- P_RESETMAXSIZE - Static variable in class ec.rule.RuleSetConstraints
-
- P_RESETMINSIZE - Static variable in class ec.rule.RuleSetConstraints
-
- P_RESETSIZE - Static variable in class ec.rule.RuleSetConstraints
-
- P_RESTART_TYPE - Static variable in class ec.evolve.RandomRestarts
-
- P_RESTART_UPPERBOUND - Static variable in class ec.evolve.RandomRestarts
-
- P_RETRIES - Static variable in class ec.breed.UniquePipeline
-
- P_RETRIES - Static variable in class ec.Subpopulation
-
- P_RETURNINDIVIDUALS - Static variable in class ec.eval.Slave
-
- P_RETURNS - Static variable in class ec.gp.GPNodeConstraints
-
- P_RETURNS - Static variable in class ec.gp.GPTreeConstraints
-
- P_ROOT_PROBABILITY - Static variable in class ec.gp.koza.KozaNodeSelector
-
- P_RULE - Static variable in class ec.rule.Rule
-
- P_RULE - Static variable in class ec.rule.RuleDefaults
-
- P_RULE - Static variable in class ec.rule.RuleSetConstraints
-
num rulesets
- P_RULECONSTRAINTS - Static variable in class ec.rule.RuleInitializer
-
- P_RULESET - Static variable in class ec.rule.RuleIndividual
-
- P_RULESET - Static variable in class ec.rule.RuleSet
-
- P_RULESETCONSTRAINTS - Static variable in class ec.rule.RuleInitializer
-
- P_RULESPECIES - Static variable in class ec.rule.RuleSpecies
-
- P_RUNEVOLVE - Static variable in class ec.eval.Slave
-
Should slave run its own evolutionary process?
- P_RUNS - Static variable in class ec.eval.MetaProblem
-
- P_RUNTIME - Static variable in class ec.eval.Slave
-
Time to run evolution on the slaves in seconds
- P_SCALED_FITNESS_FLOOR - Static variable in class ec.select.SigmaScalingSelection
-
Scaled fitness floor
- P_SEED - Static variable in class ec.Evolve
-
seed parameter
- P_SEGMENT - Static variable in class ec.vector.IntegerVectorSpecies
-
- P_SEGMENT - Static variable in class ec.vector.VectorSpecies
-
- P_SEGMENT_END - Static variable in class ec.vector.IntegerVectorSpecies
-
- P_SEGMENT_END - Static variable in class ec.vector.VectorSpecies
-
- P_SEGMENT_START - Static variable in class ec.vector.IntegerVectorSpecies
-
- P_SEGMENT_START - Static variable in class ec.vector.VectorSpecies
-
- P_SEGMENT_TYPE - Static variable in class ec.vector.IntegerVectorSpecies
-
- P_SEGMENT_TYPE - Static variable in class ec.vector.VectorSpecies
-
- P_SELECT - Static variable in class ec.select.MultiSelection
-
- P_SELECT - Static variable in class ec.select.SelectDefaults
-
- P_SELECT_METHOD - Static variable in class ec.exchange.InterPopulationExchange
-
The selection method for sending individuals to other islands
- P_SELECT_METHOD - Static variable in class ec.exchange.IslandExchange
-
The selection method for sending individuals to other islands
- P_SELECT_TO_DIE_METHOD - Static variable in class ec.exchange.InterPopulationExchange
-
The selection method for deciding individuals to be replaced by immigrants
- P_SELECT_TO_DIE_METHOD - Static variable in class ec.exchange.IslandExchange
-
The selection method for deciding individuals to be replaced by immigrants
- P_SELECTION_METHOD_CURRENT - Static variable in class ec.coevolve.MultiPopCoevolutionaryEvaluator
-
- P_SELECTION_METHOD_PREV - Static variable in class ec.coevolve.MultiPopCoevolutionaryEvaluator
-
- P_SEQUENTIAL_BREEDING - Static variable in class ec.simple.SimpleBreeder
-
- P_SERVER_ADDRESS - Static variable in class ec.exchange.IslandExchange
-
The server address
- P_SERVER_PORT - Static variable in class ec.exchange.IslandExchange
-
The server port
- P_SET - Static variable in class ec.gp.GPInitializer
-
- P_SET_RANDOM - Static variable in class ec.eval.MetaProblem
-
- P_SHORTVECTORINDIVIDUAL - Static variable in class ec.vector.ShortVectorIndividual
-
- P_SHUFFLE - Static variable in class ec.select.SUSSelection
-
- P_SIGMA - Static variable in class ec.eda.CMAESSpecies
-
- P_SIGMA_SCALING - Static variable in class ec.select.SigmaScalingSelection
-
Default base
- P_SILENT - Static variable in class ec.eval.Slave
-
- P_SILENT - Static variable in class ec.Evolve
-
Should we muzzle stdout and stderr?
- P_SILENT - Static variable in class ec.Statistics
-
- P_SILENT_FILE - Static variable in class ec.Statistics
-
- P_SILENT_FRONT_FILE - Static variable in class ec.multiobjective.MultiObjectiveStatistics
-
- P_SILENT_PRINT - Static variable in class ec.Statistics
-
- P_SIMPLE - Static variable in class ec.simple.SimpleDefaults
-
- P_SIZE - Static variable in class ec.exchange.InterPopulationExchange
-
The number of emigrants to be sent
- P_SIZE - Static variable in class ec.gp.GPFunctionSet
-
- P_SIZE - Static variable in class ec.gp.GPInitializer
-
- P_SIZE - Static variable in class ec.gp.GPNodeBuilder
-
- P_SIZE - Static variable in class ec.gp.GPNodeConstraints
-
- P_SIZE - Static variable in class ec.gp.GPSetType
-
- P_SIZE - Static variable in class ec.gp.GPTreeConstraints
-
- P_SIZE - Static variable in class ec.parsimony.BucketTournamentSelection
-
Tournament size parameter
- P_SIZE - Static variable in class ec.parsimony.DoubleTournamentSelection
-
size parameter
- P_SIZE - Static variable in class ec.parsimony.RatioBucketTournamentSelection
-
size parameter
- P_SIZE - Static variable in class ec.Population
-
- P_SIZE - Static variable in class ec.rule.RuleInitializer
-
- P_SIZE - Static variable in class ec.select.BestSelection
-
- P_SIZE - Static variable in class ec.select.TournamentSelection
-
size parameter
- P_SIZE2 - Static variable in class ec.parsimony.DoubleTournamentSelection
-
- P_SIZEFAIR - Static variable in class ec.gp.breed.SizeFairCrossoverPipeline
-
- P_SOURCE - Static variable in class ec.BreedingPipeline
-
Standard parameter for individual-selectors associated with a BreedingPipeline
- P_SPATIAL - Static variable in class ec.spatial.SpatialDefaults
-
- P_SPECIES - Static variable in class ec.Subpopulation
-
- P_STACK - Static variable in class ec.gp.GPProblem
-
- P_START - Static variable in class ec.evolve.RandomRestarts
-
- P_STARTING_TEMPERATURE - Static variable in class ec.select.BoltzmannSelection
-
Starting temperature parameter
- P_STATE - Static variable in class ec.Evolve
-
state parameter
- P_STATISTICS - Static variable in class ec.EvolutionState
-
- P_STATISTICS_FILE - Static variable in class ec.simple.SimpleShortStatistics
-
- P_STATISTICS_FILE - Static variable in class ec.simple.SimpleStatistics
-
log file parameter
- P_STATISTICS_MODULUS - Static variable in class ec.simple.SimpleShortStatistics
-
- P_STDEV - Static variable in class ec.vector.FloatVectorSpecies
-
- P_STEADYSTATE - Static variable in class ec.steadystate.SteadyStateDefaults
-
- P_SUBPOP - Static variable in class ec.coevolve.MultiPopCoevolutionaryEvaluator
-
- P_SUBPOP - Static variable in class ec.exchange.InterPopulationExchange
-
The subpopulation delimiter
- P_SUBPOP - Static variable in class ec.Population
-
- P_SUBPOPSIZE - Static variable in class ec.Subpopulation
-
- P_SUBPOPULATION - Static variable in class ec.Subpopulation
-
- P_SUS - Static variable in class ec.select.SUSSelection
-
Default base
- P_SWITCHAT - Static variable in class ec.breed.GenerationSwitchPipeline
-
- P_TERMINAL_PROBABILITY - Static variable in class ec.gp.koza.KozaNodeSelector
-
- P_TITLE - Static variable in class ec.display.chart.ChartableStatistics
-
- P_TOP - Static variable in class ec.select.GreedyOverselection
-
- P_TOROIDAL - Static variable in class ec.spatial.Spatial1DSubpopulation
-
This parameter stipulates whether the world is toroidal or not.
- P_TOSS - Static variable in class ec.gp.breed.SizeFairCrossoverPipeline
-
- P_TOSS - Static variable in class ec.gp.koza.CrossoverPipeline
-
- P_TOSS - Static variable in class ec.rule.breed.RuleCrossoverPipeline
-
- P_TOSS - Static variable in class ec.vector.breed.ListCrossoverPipeline
-
- P_TOSS - Static variable in class ec.vector.breed.VectorCrossoverPipeline
-
- P_TOURNAMENT - Static variable in class ec.parsimony.BucketTournamentSelection
-
Default base
- P_TOURNAMENT - Static variable in class ec.parsimony.DoubleTournamentSelection
-
default base
- P_TOURNAMENT - Static variable in class ec.parsimony.LexicographicTournamentSelection
-
default base
- P_TOURNAMENT - Static variable in class ec.select.TournamentSelection
-
default base
- P_TREE - Static variable in class ec.gp.GPBreedingPipeline
-
Standard parameter for tree fixing
- P_TREE - Static variable in class ec.gp.GPIndividual
-
- P_TREE - Static variable in class ec.gp.GPTree
-
- P_TREECONSTRAINTS - Static variable in class ec.gp.GPInitializer
-
- P_TREECONSTRAINTS - Static variable in class ec.gp.GPTree
-
- P_TRUEDISTRIBUTION - Static variable in class ec.gp.build.Uniform
-
- P_TYPE - Static variable in class ec.eval.MetaProblem
-
- P_TYPE - Static variable in class ec.gp.GPInitializer
-
- P_TYPE - Static variable in class ec.spatial.SpatialTournamentSelection
-
Selection procedure.
- P_UNIFORM - Static variable in class ec.gp.build.Uniform
-
- P_UNIFORM_MAX - Static variable in class ec.vector.VectorSpecies
-
- P_UNIFORM_MIN - Static variable in class ec.vector.VectorSpecies
-
- P_UNIQUE - Static variable in class ec.breed.UniquePipeline
-
- P_USEC - Static variable in class ec.gp.GPTree
-
- P_USEGRAPHVIZ - Static variable in class ec.gp.GPTree
-
- P_USELATEX - Static variable in class ec.gp.GPTree
-
- P_USEOPS - Static variable in class ec.gp.GPTree
-
- P_USEVARS - Static variable in class ec.gp.GPTree
-
- P_VAL - Static variable in class ec.eval.MetaProblem
-
- P_VECTOR - Static variable in class ec.vector.VectorDefaults
-
- P_VECTORSPECIES - Static variable in class ec.vector.VectorSpecies
-
- P_VELOCITY_COEFFICIENT - Static variable in class ec.pso.PSOBreeder
-
- P_WEIGHTS - Static variable in class ec.eda.CMAESSpecies
-
- P_XAXIS - Static variable in class ec.display.chart.ChartableStatistics
-
- p_y - Variable in class ec.gp.build.PTCFunctionSet
-
cache of nonterminal selection probabilities -- dense array
[size-1][type].
- P_YAXIS - Static variable in class ec.display.chart.ChartableStatistics
-
- param - Variable in class ec.util.Parameter
-
- ParamClassLoadException - Exception in ec.util
-
This exception is thrown by the Parameter Database when it fails to
locate and load a class specified by a given parameter as requested.
- ParamClassLoadException(String) - Constructor for exception ec.util.ParamClassLoadException
-
- Parameter - Class in ec.util
-
A Parameter is an object which the ParameterDatabase class
uses as a key to associate with strings, forming a key-value pair.
- Parameter(String[]) - Constructor for class ec.util.Parameter
-
Creates a new parameter by joining the path items in s into a single path.
- Parameter(String) - Constructor for class ec.util.Parameter
-
Creates a new parameter from the single path item in s.
- Parameter(String, String[]) - Constructor for class ec.util.Parameter
-
Creates a new parameter from the path item in s, plus the path items in s2.
- ParameterDatabase - Class in ec.util
-
This extension of the Properties class allows you to set, get, and delete
Parameters in a hierarchical tree-like database.
- ParameterDatabase() - Constructor for class ec.util.ParameterDatabase
-
Creates an empty parameter database.
- ParameterDatabase(Dictionary) - Constructor for class ec.util.ParameterDatabase
-
Creates a new parameter database from the given Dictionary.
- ParameterDatabase(String, Class, String[]) - Constructor for class ec.util.ParameterDatabase
-
Creates a new parameter database from a given database file and argv
list.
- ParameterDatabase(String, Class) - Constructor for class ec.util.ParameterDatabase
-
Creates a new parameter database loaded from a parameter file located relative to a class file,
wherever the class file may be (such as in a jar).
- ParameterDatabase(InputStream) - Constructor for class ec.util.ParameterDatabase
-
Creates a new parameter database loaded from the given stream.
- ParameterDatabase(File) - Constructor for class ec.util.ParameterDatabase
-
Creates a new parameter database tree from a given database file and its
parent files.
- ParameterDatabase(File, String[]) - Constructor for class ec.util.ParameterDatabase
-
Creates a new parameter database from a given database file and argv
list.
- ParameterDatabaseEvent - Class in ec.util
-
- ParameterDatabaseEvent(Object, Parameter, String, int) - Constructor for class ec.util.ParameterDatabaseEvent
-
For ParameterDatabase events.
- ParameterDatabaseTreeModel - Class in ec.util
-
- ParameterDatabaseTreeModel(TreeNode) - Constructor for class ec.util.ParameterDatabaseTreeModel
-
- ParameterDatabaseTreeModel(TreeNode, boolean) - Constructor for class ec.util.ParameterDatabaseTreeModel
-
- parameters - Variable in class ec.EvolutionState
-
The parameter database (threadsafe).
- ParametersPanel - Class in ec.display
-
- ParametersPanel(Console) - Constructor for class ec.display.ParametersPanel
-
This is the default constructor
- ParameterValue - Class in ec.display
-
- ParameterValue(String) - Constructor for class ec.display.ParameterValue
-
- parent - Variable in class ec.gp.GPNode
-
The GPNode's parent.
- parentPopulation - Variable in class ec.es.MuCommaLambdaBreeder
-
- parents - Variable in class ec.gp.breed.SizeFairCrossoverPipeline
-
Temporary holding place for parents
- parents - Variable in class ec.gp.koza.CrossoverPipeline
-
Temporary holding place for parents
- parents - Variable in class ec.vector.breed.ListCrossoverPipeline
-
- parentType(GPInitializer) - Method in class ec.gp.GPNode
-
Returns the argument type of the slot that I fit into in my parent.
- paretoDominates(MultiObjectiveFitness) - Method in class ec.multiobjective.MultiObjectiveFitness
-
Returns true if I'm better than _fitness.
- parseGenotype(EvolutionState, LineNumberReader) - Method in class ec.gp.GPIndividual
-
- parseGenotype(EvolutionState, LineNumberReader) - Method in class ec.Individual
-
This method is used only by the default version of readIndividual(state,reader),
and it is intended to be overridden to parse in that part of the individual that
was outputted in the genotypeToString() method.
- parseGenotype(EvolutionState, LineNumberReader) - Method in class ec.rule.RuleIndividual
-
Overridden for the RuleIndividual genotype.
- parseGenotype(EvolutionState, LineNumberReader) - Method in class ec.vector.BitVectorIndividual
-
- parseGenotype(EvolutionState, LineNumberReader) - Method in class ec.vector.ByteVectorIndividual
-
- parseGenotype(EvolutionState, LineNumberReader) - Method in class ec.vector.DoubleVectorIndividual
-
- parseGenotype(EvolutionState, LineNumberReader) - Method in class ec.vector.FloatVectorIndividual
-
- parseGenotype(EvolutionState, LineNumberReader) - Method in class ec.vector.GeneVectorIndividual
-
- parseGenotype(EvolutionState, LineNumberReader) - Method in class ec.vector.IntegerVectorIndividual
-
- parseGenotype(EvolutionState, LineNumberReader) - Method in class ec.vector.LongVectorIndividual
-
- parseGenotype(EvolutionState, LineNumberReader) - Method in class ec.vector.ShortVectorIndividual
-
- parser_prototype - Variable in class ec.gp.ge.GESpecies
-
The prototypical parser used to parse the grammars.
- parseRules(EvolutionState, BufferedReader, GPFunctionSet) - Method in class ec.gp.ge.GrammarParser
-
Parses the rules from a grammar and returns the resulting GrammarRuleNode root.
- parseSexp(ArrayList, GrammarParser) - Method in class ec.gp.ge.GESpecies
-
The LL(1) parsing algorithm to parse the lisp tree, the lisp tree is actually
fed as a flattened list, the parsing code uses the "exact" (and as-is) procedure
described in the dragon book.
- Particle - Class in ec.pso
-
Particle is a DoubleVectorIndividual with additional statistical information
necessary to perform Particle Swarm Optimization.
- Particle() - Constructor for class ec.pso.Particle
-
- partitionIntoParetoFront(Individual[], ArrayList, ArrayList) - Static method in class ec.multiobjective.MultiObjectiveFitness
-
Divides an array of Individuals into the Pareto front and the "nonFront" (everyone else).
- partitionIntoRanks(Individual[]) - Static method in class ec.multiobjective.MultiObjectiveFitness
-
Divides inds into pareto front ranks (each an ArrayList), and returns them, in order,
stored in an ArrayList.
- passes - Variable in class ec.gp.ge.GESpecies
-
The number of passes permitted through the genome if we're wrapping.
- pathLength(int) - Method in class ec.gp.GPNode
-
Returns the path length of the tree, which is the sum of all paths from all nodes to the root.
- pc - Variable in class ec.eda.CMAESSpecies
-
The p_c evolution path vector.
- performCoevolutionaryEvaluation(EvolutionState, Population, GroupedProblemForm) - Method in class ec.coevolve.MultiPopCoevolutionaryEvaluator
-
- personalBestFitness - Variable in class ec.pso.Particle
-
- personalBestGenome - Variable in class ec.pso.Particle
-
- personalCoeff - Variable in class ec.pso.PSOBreeder
-
- PF - Variable in class ec.de.Rand1EitherOrDEBreeder
-
- pickFromDistribution(float[], float) - Static method in class ec.util.RandomChoice
-
Picks a random item from an array of probabilities,
normalized and summed as follows: For example,
if four probabilities are {0.3, 0.2, 0.1, 0.4}, then
they should get normalized and summed by the outside owners
as: {0.3, 0.5, 0.6, 1.0}.
- pickFromDistribution(float[], float, int) - Static method in class ec.util.RandomChoice
-
Deprecated.
- pickFromDistribution(double[], double) - Static method in class ec.util.RandomChoice
-
Picks a random item from an array of probabilities,
normalized and summed as follows: For example,
if four probabilities are {0.3, 0.2, 0.1, 0.4}, then
they should get normalized and summed by the outside owners
as: {0.3, 0.5, 0.6, 1.0}.
- pickFromDistribution(double[], double, int) - Static method in class ec.util.RandomChoice
-
Deprecated.
- pickFromDistribution(Object[], RandomChoiceChooser, float) - Static method in class ec.util.RandomChoice
-
Picks a random item from an array of objects, each with an
associated probability that is accessed by taking an object
and passing it to chooser.getProbability(obj).
- pickFromDistribution(Object[], RandomChoiceChooser, float, int) - Static method in class ec.util.RandomChoice
-
Deprecated.
- pickFromDistribution(Object[], RandomChoiceChooserD, double) - Static method in class ec.util.RandomChoice
-
Picks a random item from an array of objects, each with an
associated probability that is accessed by taking an object
and passing it to chooser.getProbability(obj).
- pickFromDistribution(Object[], RandomChoiceChooserD, double, int) - Static method in class ec.util.RandomChoice
-
Deprecated.
- pickGrowProbability - Variable in class ec.gp.koza.HalfBuilder
-
The likelihood of using GROW over FULL.
- pickNode(EvolutionState, int, int, GPIndividual, GPTree) - Method in interface ec.gp.GPNodeSelector
-
Picks a node at random from tree and returns it.
- pickNode(EvolutionState, int, int, GPIndividual, GPTree) - Method in class ec.gp.koza.KozaNodeSelector
-
- pickRandom(BreedingSource[], double) - Static method in class ec.BreedingSource
-
Picks a random source from an array of sources, with their
probabilities normalized and summed as follows: For example,
if four
breeding source probabilities are {0.3, 0.2, 0.1, 0.4}, then
they should get normalized and summed by the outside owners
as: {0.3, 0.5, 0.6, 1.0}.
- pickSize(EvolutionState, int, int, int) - Method in class ec.gp.build.Uniform
-
- pickSize(EvolutionState, int) - Method in class ec.gp.GPNodeBuilder
-
Assuming that either minSize and maxSize, or sizeDistribution, is defined,
picks a random size from minSize...maxSize inclusive, or randomly
from sizeDistribution.
- pickSize(EvolutionState, int) - Method in class ec.rule.RuleSetConstraints
-
Assuming that either resetMinSize and resetMaxSize, or sizeDistribution, is defined,
picks a random size from resetMinSize...resetMaxSize inclusive, or randomly
from sizeDistribution.
- pickWorst - Variable in class ec.parsimony.BucketTournamentSelection
-
Do we pick the worst instead of the best?
- pickWorst - Variable in class ec.parsimony.DoubleTournamentSelection
-
Do we pick the worst instead of the best?
- pickWorst - Variable in class ec.parsimony.RatioBucketTournamentSelection
-
Do we pick the worst instead of the best?
- pickWorst - Variable in class ec.select.BestSelection
-
Do we pick the worst instead of the best?
- pickWorst - Variable in class ec.select.TournamentSelection
-
Do we pick the worst instead of the best?
- pickWorst2 - Variable in class ec.parsimony.DoubleTournamentSelection
-
- PIPE - Static variable in class ec.gp.ge.GrammarParser
-
- pipe_prototype - Variable in class ec.Species
-
The prototypical breeding pipeline for this species.
- polynomialIsAlternative - Variable in class ec.vector.FloatVectorSpecies
-
Whether the Polynomial Mutation method is the "alternative" method, per gene.
- polynomialIsAlternative(int) - Method in class ec.vector.FloatVectorSpecies
-
- polynomialMutate(EvolutionState, MersenneTwisterFast, double, boolean, boolean) - Method in class ec.vector.DoubleVectorIndividual
-
This function is broken out to keep it identical to NSGA-II's mutation.c code.
- polynomialMutate(EvolutionState, MersenneTwisterFast, float, boolean, boolean) - Method in class ec.vector.FloatVectorIndividual
-
This function is broken out to keep it identical to NSGA-II's mutation.c code.
- pool - Static variable in class ec.eval.Slave
-
- pool - Variable in class ec.simple.SimpleBreeder
-
- pool - Variable in class ec.simple.SimpleEvaluator
-
- pop(int) - Method in class ec.gp.ADFStack
-
Pops off n items from the stack, if possible.
- pop() - Method in class ec.util.Parameter
-
Returns a new parameter with one path item popped off the end.
- popn(int) - Method in class ec.util.Parameter
-
Returns a new parameter with n path items popped off the end.
- populate(EvolutionState, int) - Method in class ec.Population
-
Populates the population with new random individuals.
- populate(EvolutionState, int) - Method in class ec.Subpopulation
-
- populatePredictiveParseTable(GrammarNode) - Method in class ec.gp.ge.GrammarParser
-
Now populate the predictive-parse table, this procedure reads
hash-maps/tables for the grammar-rule indices, PREDICT-SETs etc,
and assigns the corresponding values in the predictive-parse table.
- population - Variable in class ec.EvolutionState
-
The current population.
- Population - Class in ec
-
A Population is the repository for all the Individuals being bred or
evaluated in the evolutionary run at a given time.
- Population() - Constructor for class ec.Population
-
- portrayIndividual(EvolutionState, Individual) - Method in class ec.display.portrayal.IndividualPortrayal
-
- portrayIndividual(EvolutionState, Individual) - Method in class ec.display.portrayal.SimpleIndividualPortrayal
-
- pos - Variable in class ec.util.DecodeReturn
-
The DecodeReturn new position in the string.
- possiblyRestoreFromCheckpoint(String[]) - Static method in class ec.Evolve
-
Restores an EvolutionState from checkpoint if "-checkpoint FILENAME" is in the command-line arguments.
- postAnnouncements - Variable in class ec.util.Log
-
Should the log post announcements?
- postBreedingExchangePopulation(EvolutionState) - Method in class ec.exchange.InterPopulationExchange
-
- postBreedingExchangePopulation(EvolutionState) - Method in class ec.exchange.IslandExchange
-
- postBreedingExchangePopulation(EvolutionState) - Method in class ec.Exchanger
-
Performs exchanges after the population has been bred but before it has been evaluated,
once every generation (or pseudogeneration).
- postBreedingExchangePopulation(EvolutionState) - Method in class ec.simple.SimpleExchanger
-
Simply returns state.population.
- postBreedingStatistics(EvolutionState) - Method in class ec.simple.SimpleShortStatistics
-
- postBreedingStatistics(EvolutionState) - Method in class ec.Statistics
-
GENERATIONAL: Called immediately after breeding occurs.
- postCheckpointStatistics(EvolutionState) - Method in class ec.Statistics
-
Called immediately after checkpointing occurs.
- postCheckpointStatistics(EvolutionState) - Method in interface ec.steadystate.SteadyStateStatisticsForm
-
Called immediately after checkpointing occurs.
- postEvaluationStatistics(EvolutionState) - Method in class ec.simple.SimpleShortStatistics
-
Prints out the statistics, but does not end with a println --
this lets overriding methods print additional statistics on the same line
- postEvaluationStatistics(EvolutionState) - Method in class ec.simple.SimpleStatistics
-
- postEvaluationStatistics(EvolutionState) - Method in class ec.Statistics
-
GENERATIONAL: Called immediately after evaluation occurs.
- postEvolution(EvolutionStateEvent) - Method in interface ec.display.EvolutionStateListener
-
- postEvolution(EvolutionStateEvent) - Method in class ec.display.SubpopulationPanel
-
- postInitializationStatistics(EvolutionState) - Method in class ec.gp.koza.KozaShortStatistics
-
- postInitializationStatistics(EvolutionState) - Method in class ec.simple.SimpleShortStatistics
-
- postInitializationStatistics(EvolutionState) - Method in class ec.simple.SimpleStatistics
-
- postInitializationStatistics(EvolutionState) - Method in class ec.Statistics
-
GENERATIONAL: Called immediately after population initialization occurs.
- postPostBreedingExchangeStatistics(EvolutionState) - Method in class ec.Statistics
-
Called immediately after the post-breeding exchange occurs.
- postPostBreedingExchangeStatistics(EvolutionState) - Method in interface ec.steadystate.SteadyStateStatisticsForm
-
Called immediately after the post-breeding exchange occurs.
- postPreBreedingExchangeStatistics(EvolutionState) - Method in class ec.Statistics
-
Called immediately after the pre-breeding exchange occurs.
- postPreBreedingExchangeStatistics(EvolutionState) - Method in interface ec.steadystate.SteadyStateStatisticsForm
-
Called immediately after the pre-breeding exchange occurs.
- postProcess(Population, Population, EvolutionState) - Method in class ec.es.MuCommaLambdaBreeder
-
A hook for Mu+Lambda, not used in Mu,Lambda
- postProcess(Population, Population, EvolutionState) - Method in class ec.es.MuPlusLambdaBreeder
-
- postProcessFunctionSet() - Method in class ec.gp.GPFunctionSet
-
Sets up the arrays based on the hashtables
- postprocessIndividual(EvolutionState, int) - Method in class ec.rule.RuleIndividual
-
Called by pipelines after they've modified the individual and
it might need to be "fixed" -- basically a hook for you to override.
- postprocessPopulation(EvolutionState, Population, boolean[], boolean) - Method in interface ec.coevolve.GroupedProblemForm
-
Finish processing the population (such as fitness information) after evaluation.
- postprocessPopulation(EvolutionState, Population, boolean[], boolean) - Method in class ec.eval.MasterProblem
-
- postprocessPopulation(EvolutionState, Population, boolean[], boolean) - Method in class ec.gp.ge.GEProblem
-
- postprocessRules(EvolutionState, int) - Method in class ec.rule.RuleSet
-
Should be called by pipelines to "fix up" the rulesets after they have been
mutated or crossed over.
- postProcessSetType(int) - Method in class ec.gp.GPSetType
-
Sets up the packed and sparse arrays based on the hashtable
- postProcessTypes() - Method in class ec.gp.GPInitializer
-
Assigns unique integers to each atomic type, and sets up compatibility
arrays for set types.
- preBreedingExchangePopulation(EvolutionState) - Method in class ec.exchange.InterPopulationExchange
-
- preBreedingExchangePopulation(EvolutionState) - Method in class ec.exchange.IslandExchange
-
- preBreedingExchangePopulation(EvolutionState) - Method in class ec.Exchanger
-
Performs exchanges after the population has been evaluated but before it has been bred,
once every generation (or pseudogeneration).
- preBreedingExchangePopulation(EvolutionState) - Method in class ec.simple.SimpleExchanger
-
Simply returns state.population.
- preBreedingStatistics(EvolutionState) - Method in class ec.simple.SimpleShortStatistics
-
- preBreedingStatistics(EvolutionState) - Method in class ec.Statistics
-
GENERATIONAL: Called immediately before breeding occurs.
- preCheckpointStatistics(EvolutionState) - Method in class ec.Statistics
-
Called immediately before checkpointing occurs.
- preCheckpointStatistics(EvolutionState) - Method in interface ec.steadystate.SteadyStateStatisticsForm
-
Called immediately before checkpointing occurs.
- preEvaluationStatistics(EvolutionState) - Method in class ec.evolve.RandomRestarts
-
Checks the clock; if it's time to restart, we repopulate the population.
- preEvaluationStatistics(EvolutionState) - Method in class ec.parsimony.TarpeianStatistics
-
Marks a proportion (killProportion) of individuals with above-average size (within their own subpopulation) to a minimum value.
- preEvaluationStatistics(EvolutionState) - Method in class ec.simple.SimpleShortStatistics
-
- preEvaluationStatistics(EvolutionState) - Method in class ec.Statistics
-
GENERATIONAL: Called immediately before evaluation occurs.
- preInitializationStatistics(EvolutionState) - Method in class ec.simple.SimpleShortStatistics
-
- preInitializationStatistics(EvolutionState) - Method in class ec.Statistics
-
Called immediately before population initialization occurs.
- prepareADF(ADF, GPProblem) - Method in class ec.gp.ADFContext
-
Increases arguments to accommodate space if necessary.
- prepareADM(ADM) - Method in class ec.gp.ADFContext
-
Sets adf to a
- prepareDEBreeder(EvolutionState) - Method in class ec.de.DEBreeder
-
- preparePipeline(Object) - Method in class ec.BreedingPipeline
-
- preparePipeline(Object) - Method in class ec.BreedingSource
-
A hook which should be passed to all your subsidiary breeding
sources.
- preparePipeline(Object) - Method in class ec.select.MultiSelection
-
- prepareStatistics(EvolutionState) - Method in class ec.gp.koza.KozaShortStatistics
-
- prepareStatistics(EvolutionState) - Method in class ec.simple.SimpleShortStatistics
-
- prepareToBreed(EvolutionState, int) - Method in class ec.steadystate.SteadyStateBreeder
-
- prepareToEvaluate(EvolutionState, int) - Method in class ec.eval.MasterProblem
-
- prepareToEvaluate(EvolutionState, int) - Method in class ec.gp.ge.GEProblem
-
- prepareToEvaluate(EvolutionState, int) - Method in class ec.Problem
-
May be called by the Evaluator prior to a series of individuals to
evaluate, and then ended with a finishEvaluating(...).
- prepareToEvaluate(EvolutionState, int) - Method in class ec.steadystate.SteadyStateEvaluator
-
- prepareToProduce(EvolutionState, int, int) - Method in class ec.breed.BufferedBreedingPipeline
-
- prepareToProduce(EvolutionState, int, int) - Method in class ec.breed.UniquePipeline
-
- prepareToProduce(EvolutionState, int, int) - Method in class ec.BreedingPipeline
-
- prepareToProduce(EvolutionState, int, int) - Method in class ec.BreedingSource
-
Called before produce(...), usually once a generation, or maybe only
once if you're doing steady-state evolution, to let the breeding source
"warm up" prior to producing.
- prepareToProduce(EvolutionState, int, int) - Method in class ec.es.ESSelection
-
- prepareToProduce(EvolutionState, int, int) - Method in class ec.parsimony.BucketTournamentSelection
-
Prepare to produce: create the buckets!!!!
- prepareToProduce(EvolutionState, int, int) - Method in class ec.parsimony.RatioBucketTournamentSelection
-
Prepare to produce: create the buckets!!!!
- prepareToProduce(EvolutionState, int, int) - Method in class ec.select.BestSelection
-
- prepareToProduce(EvolutionState, int, int) - Method in class ec.select.BoltzmannSelection
-
- prepareToProduce(EvolutionState, int, int) - Method in class ec.select.FitProportionateSelection
-
- prepareToProduce(EvolutionState, int, int) - Method in class ec.select.GreedyOverselection
-
- prepareToProduce(EvolutionState, int, int) - Method in class ec.select.MultiSelection
-
- prepareToProduce(EvolutionState, int, int) - Method in class ec.select.SigmaScalingSelection
-
- prepareToProduce(EvolutionState, int, int) - Method in class ec.select.SUSSelection
-
- prepareToProduce(EvolutionState, int, int) - Method in class ec.SelectionMethod
-
A default version of prepareToProduce which does nothing.
- prePostBreedingExchangeStatistics(EvolutionState) - Method in class ec.Statistics
-
Called immediately before the post-breeding exchange occurs.
- prePostBreedingExchangeStatistics(EvolutionState) - Method in interface ec.steadystate.SteadyStateStatisticsForm
-
Called immediately before the post-breeding exchange occurs.
- prePreBreedingExchangeStatistics(EvolutionState) - Method in class ec.Statistics
-
Called immediately before the pre-breeding exchange occurs.
- prePreBreedingExchangeStatistics(EvolutionState) - Method in interface ec.steadystate.SteadyStateStatisticsForm
-
Called immediately before the pre-breeding exchange occurs.
- preprocess(EvolutionState, int) - Method in class ec.gp.build.Uniform
-
- preprocessIndividual(EvolutionState, int) - Method in class ec.rule.RuleIndividual
-
Called by pipelines before they've modified the individual and
it might need to be "fixed" -- basically a hook for you to override.
- preprocessPopulation(EvolutionState, Population, boolean[], boolean) - Method in interface ec.coevolve.GroupedProblemForm
-
Set up the population pop (such as fitness information) prior to evaluation.
- preprocessPopulation(EvolutionState, Population, boolean[], boolean) - Method in class ec.eval.MasterProblem
-
- preprocessPopulation(EvolutionState, Population, boolean[], boolean) - Method in class ec.gp.ge.GEProblem
-
- preprocessRules(EvolutionState, int) - Method in class ec.rule.RuleSet
-
Should be called by pipelines to "fix up" the rulesets before they have been
mutated or crossed over.
- previousPopulation - Variable in class ec.de.DEBreeder
-
the previous population is stored in order to have parents compete directly with their children
- primeGenerator(MersenneTwisterFast) - Static method in class ec.Evolve
-
Primes the generator.
- print(String, int, Log) - Method in class ec.util.Output
-
Prints a non-announcement message to a given log, with a
certain verbosity.
- print(String, int, int) - Method in class ec.util.Output
-
Prints a non-announcement message to a given log, with a
certain verbosity.
- print(String, int) - Method in class ec.util.Output
-
Prints a non-announcement message to a given log.
- print(String, int, int[]) - Method in class ec.util.Output
-
- print(String, int[]) - Method in class ec.util.Output
-
Prints a non-announcement message to the given logs,
with a certain verbosity.
- PRINT_PARAMS - Static variable in class ec.util.ParameterDatabase
-
- PRINT_STYLE_C - Static variable in class ec.gp.GPTree
-
- PRINT_STYLE_DOT - Static variable in class ec.gp.GPTree
-
- PRINT_STYLE_LATEX - Static variable in class ec.gp.GPTree
-
- PRINT_STYLE_LISP - Static variable in class ec.gp.GPTree
-
- printExtraPopStatisticsAfter(EvolutionState) - Method in class ec.simple.SimpleShortStatistics
-
- printExtraPopStatisticsBefore(EvolutionState) - Method in class ec.gp.koza.KozaShortStatistics
-
- printExtraPopStatisticsBefore(EvolutionState) - Method in class ec.simple.SimpleShortStatistics
-
- printExtraSubpopStatisticsAfter(EvolutionState, int) - Method in class ec.simple.SimpleShortStatistics
-
- printExtraSubpopStatisticsBefore(EvolutionState, int) - Method in class ec.gp.koza.KozaShortStatistics
-
- printExtraSubpopStatisticsBefore(EvolutionState, int) - Method in class ec.simple.SimpleShortStatistics
-
- printFitness(EvolutionState, int) - Method in class ec.Fitness
-
Should print the fitness out in a computer-readable fashion,
with a verbosity of Output.V_NO_GENERAL.
- printFitness(EvolutionState, int, int) - Method in class ec.Fitness
-
- printFitness(EvolutionState, PrintWriter) - Method in class ec.Fitness
-
Should print the fitness out in a computer-readable fashion,
using writer.println(...).
- printFitnessForHumans(EvolutionState, int) - Method in class ec.Fitness
-
Should print the fitness out fashion pleasing for humans to read,
with a verbosity of Output.V_NO_GENERAL.
- printFitnessForHumans(EvolutionState, int, int) - Method in class ec.Fitness
-
- printGene(EvolutionState, int, int) - Method in class ec.vector.Gene
-
Prints the gene in a way that can be read by readGene().
- printGene(EvolutionState, PrintWriter) - Method in class ec.vector.Gene
-
Prints the gene in a way that can be read by readGene().
- printGeneForHumans(EvolutionState, int, int) - Method in class ec.vector.Gene
-
Nice printing.
- printGeneToString() - Method in class ec.vector.Gene
-
Prints the gene to a string in a fashion readable by readGeneFromString and parseable by readGene(state, reader).
- printGeneToStringForHumans() - Method in class ec.vector.Gene
-
Prints the gene to a string in a human-readable fashion.
- printIndividual(EvolutionState, int) - Method in class ec.gp.GPIndividual
-
- printIndividual(EvolutionState, PrintWriter) - Method in class ec.gp.GPIndividual
-
- printIndividual(EvolutionState, int) - Method in class ec.Individual
-
Should print the individual in a way that can be read by computer,
including its fitness, with a verbosity of Output.V_NO_GENERAL.
- printIndividual(EvolutionState, int, int) - Method in class ec.Individual
-
- printIndividual(EvolutionState, PrintWriter) - Method in class ec.Individual
-
Should print the individual in a way that can be read by computer,
including its fitness.
- printIndividual(EvolutionState, int) - Method in class ec.pso.Particle
-
- printIndividual(EvolutionState, PrintWriter) - Method in class ec.pso.Particle
-
- printIndividual(EvolutionState, int) - Method in class ec.rule.RuleIndividual
-
- printIndividual(EvolutionState, PrintWriter) - Method in class ec.rule.RuleIndividual
-
Overridden for the RuleIndividual genotype, writing each ruleset in turn.
- printIndividualForHumans(EvolutionState, int) - Method in class ec.gp.ge.GEIndividual
-
- printIndividualForHumans(EvolutionState, int) - Method in class ec.gp.GPIndividual
-
- printIndividualForHumans(EvolutionState, int) - Method in class ec.Individual
-
Should print the individual out in a pleasing way for humans,
with a verbosity of Output.V_NO_GENERAL.
- printIndividualForHumans(EvolutionState, int, int) - Method in class ec.Individual
-
- printIndividualForHumans(EvolutionState, int) - Method in class ec.rule.RuleIndividual
-
- println(String, int, boolean) - Method in class ec.util.Output
-
Prints a message to a given log.
- println(String, int, int[]) - Method in class ec.util.Output
-
- println(String, int, int) - Method in class ec.util.Output
-
- println(String, int) - Method in class ec.util.Output
-
Prints a non-announcement message to the given logs, with a verbosity of V_NO_GENERAL.
- printNode(EvolutionState, int) - Method in class ec.gp.GPNode
-
Prints out a COMPUTER-readable and Lisp-like atom for the node, which
is also suitable for readNode to read, and returns
the number of bytes in the string that you sent to the log (use print(),
not println()).
- printNode(EvolutionState, int, int) - Method in class ec.gp.GPNode
-
- printNode(EvolutionState, PrintWriter) - Method in class ec.gp.GPNode
-
Prints out a COMPUTER-readable and Lisp-like atom for the node, which
is also suitable for readNode to read, and returns
the number of bytes in the string that you sent to the log (use print(),
not println()).
- printNodeForHumans(EvolutionState, int) - Method in class ec.gp.GPNode
-
Prints out a human-readable and Lisp-like atom for the node,
and returns the number of bytes in the string that you sent
to the log (use print(),
not println()).
- printNodeForHumans(EvolutionState, int, int) - Method in class ec.gp.GPNode
-
- printPopulation(EvolutionState, int, int) - Method in class ec.Population
-
- printPopulation(EvolutionState, int) - Method in class ec.Population
-
Prints an entire population in a form readable by humans but also parseable by the computer using readPopulation(EvolutionState, LineNumberReader), with a verbosity of Output.V_NO_GENERAL.
- printPopulation(EvolutionState, PrintWriter) - Method in class ec.Population
-
Prints an entire population in a form readable by humans but also parseable by the computer using readPopulation(EvolutionState, LineNumberReader).
- printPopulationForHumans(EvolutionState, int, int) - Method in class ec.Population
-
- printPopulationForHumans(EvolutionState, int) - Method in class ec.Population
-
Prints an entire population in a form readable by humans, with a verbosity of Output.V_NO_GENERAL.
- printRootedTree(EvolutionState, int, int) - Method in class ec.gp.GPNode
-
Prints out the tree on a single line, with no ending \n, in a fashion that can
be read in later by computer.
- printRootedTree(EvolutionState, int, int, int) - Method in class ec.gp.GPNode
-
- printRootedTree(EvolutionState, PrintWriter, int) - Method in class ec.gp.GPNode
-
Prints out the tree on a single line, with no ending \n, in a fashion that can
be read in later by computer.
- printRootedTreeForHumans(EvolutionState, int, int, int) - Method in class ec.gp.GPNode
-
Prints out the tree in a readable Lisp-like multi-line fashion.
- printRootedTreeForHumans(EvolutionState, int, int, int, int) - Method in class ec.gp.GPNode
-
- printRule(EvolutionState, int) - Method in class ec.rule.Rule
-
Prints the rule in a way that can be read by readRule().
- printRule(EvolutionState, int, int) - Method in class ec.rule.Rule
-
- printRule(EvolutionState, PrintWriter) - Method in class ec.rule.Rule
-
Prints the rule in a way that can be read by readRule().
- printRuleForHumans(EvolutionState, int) - Method in class ec.rule.Rule
-
Nice printing.
- printRuleForHumans(EvolutionState, int, int) - Method in class ec.rule.Rule
-
- printRuleSet(EvolutionState, int) - Method in class ec.rule.RuleSet
-
Prints the rule set such that the computer can read it later
- printRuleSet(EvolutionState, int, int) - Method in class ec.rule.RuleSet
-
- printRuleSet(EvolutionState, PrintWriter) - Method in class ec.rule.RuleSet
-
Prints the rule set such that the computer can read it later
- printRuleSetForHumans(EvolutionState, int) - Method in class ec.rule.RuleSet
-
Prints out the rule set in a readable fashion.
- printRuleSetForHumans(EvolutionState, int, int) - Method in class ec.rule.RuleSet
-
- printRuleToString(EvolutionState) - Method in class ec.rule.Rule
-
Deprecated.
- printRuleToString() - Method in class ec.rule.Rule
-
Prints the rule to a string in a fashion readable by readRuleFromString.
- printRuleToStringForHumans() - Method in class ec.rule.Rule
-
Nice printing to a string.
- printState - Variable in class ec.util.ParameterDatabase
-
- printStyle - Variable in class ec.gp.GPTree
-
The print style of the GPTree.
- printSubpopulation(EvolutionState, int, int) - Method in class ec.Subpopulation
-
- printSubpopulation(EvolutionState, int) - Method in class ec.Subpopulation
-
Prints an entire subpopulation in a form readable by humans but also parseable by the computer using readSubpopulation(EvolutionState, LineNumberReader) with a verbosity of Output.V_NO_GENERAL.
- printSubpopulation(EvolutionState, PrintWriter) - Method in class ec.Subpopulation
-
Prints an entire subpopulation in a form readable by humans but also parseable by the computer using readSubpopulation(EvolutionState, LineNumberReader).
- printSubpopulationForHumans(EvolutionState, int, int) - Method in class ec.Subpopulation
-
- printSubpopulationForHumans(EvolutionState, int) - Method in class ec.Subpopulation
-
- printTerminalsAsVariablesInC - Variable in class ec.gp.GPTree
-
When using c to print for humans, do we print terminals as variables?
(as opposed to zero-argument functions)?
- printTree(EvolutionState, int) - Method in class ec.gp.GPTree
-
Prints out the tree in single-line fashion suitable for reading
in later by computer.
- printTree(EvolutionState, int, int) - Method in class ec.gp.GPTree
-
- printTree(EvolutionState, PrintWriter) - Method in class ec.gp.GPTree
-
Prints out the tree in single-line fashion suitable for reading
in later by computer.
- printTreeForHumans(EvolutionState, int) - Method in class ec.gp.GPTree
-
Prints out the tree in a readable Lisp-like fashion.
- printTreeForHumans(EvolutionState, int, int) - Method in class ec.gp.GPTree
-
- printTrees(EvolutionState, int) - Method in class ec.gp.GPIndividual
-
Prints just the trees of the GPIndividual.
- printTwoArgumentNonterminalsAsOperatorsInC - Variable in class ec.gp.GPTree
-
When using c to print for humans, do we print two-argument nonterminals in operator form "a op b"?
(as opposed to functions "op(a, b)")?
- probability - Variable in class ec.BreedingSource
-
The probability that this BreedingSource will be chosen
to breed over other BreedingSources.
- probabilityOfPickingSizePlusOne - Variable in class ec.select.BestSelection
-
Probablity of picking the size plus one.
- probabilityOfPickingSizePlusOne - Variable in class ec.select.TournamentSelection
-
Probablity of picking the size plus one
- probabilityOfSelection - Variable in class ec.gp.GPNodeConstraints
-
Probability of selection -- an auxillary measure mostly used by PTC1/PTC2
right now
- probabilityOfSelection - Variable in class ec.parsimony.DoubleTournamentSelection
-
What's our probability of selection? If 1.0, we always pick the "good" individual.
- probabilityOfSelection2 - Variable in class ec.parsimony.DoubleTournamentSelection
-
- problem - Variable in class ec.eval.MasterProblem
-
- problem - Variable in class ec.gp.ge.GEProblem
-
- Problem - Class in ec
-
Problem is a prototype which defines the problem against which we will
evaluate individuals in a population.
- Problem() - Constructor for class ec.Problem
-
- process(EvolutionState, int, String, int, Individual) - Method in class ec.Exchanger
-
Typically called by preBreedingExchangePopulation prior to migrating an individual.
- produce(int, int, int, int, Individual[], EvolutionState, int) - Method in class ec.breed.BufferedBreedingPipeline
-
- produce(int, int, int, int, Individual[], EvolutionState, int) - Method in class ec.breed.CheckingPipeline
-
- produce(int, int, int, int, Individual[], EvolutionState, int) - Method in class ec.breed.ForceBreedingPipeline
-
- produce(int, int, int, int, Individual[], EvolutionState, int) - Method in class ec.breed.GenerationSwitchPipeline
-
- produce(int, int, int, int, Individual[], EvolutionState, int) - Method in class ec.breed.InitializationPipeline
-
- produce(int, int, int, int, Individual[], EvolutionState, int) - Method in class ec.breed.MultiBreedingPipeline
-
- produce(int, int, int, int, Individual[], EvolutionState, int) - Method in class ec.breed.ReproductionPipeline
-
- produce(int, int, int, int, Individual[], EvolutionState, int) - Method in class ec.breed.UniquePipeline
-
- produce(int, int, int, int, Individual[], EvolutionState, int) - Method in class ec.BreedingSource
-
Produces n individuals from the given subpopulation
and puts them into inds[start...start+n-1],
where n = Min(Max(q,min),max), where q is the "typical" number of
individuals the BreedingSource produces in one shot, and returns
n.
- produce(int, EvolutionState, int) - Method in class ec.es.ESSelection
-
- produce(int, int, int, int, Individual[], EvolutionState, int) - Method in class ec.es.ESSelection
-
- produce(int, int, int, int, Individual[], EvolutionState, int) - Method in class ec.gp.breed.InternalCrossoverPipeline
-
- produce(int, int, int, int, Individual[], EvolutionState, int) - Method in class ec.gp.breed.MutateAllNodesPipeline
-
- produce(int, int, int, int, Individual[], EvolutionState, int) - Method in class ec.gp.breed.MutateDemotePipeline
-
- produce(int, int, int, int, Individual[], EvolutionState, int) - Method in class ec.gp.breed.MutateERCPipeline
-
- produce(int, int, int, int, Individual[], EvolutionState, int) - Method in class ec.gp.breed.MutateOneNodePipeline
-
- produce(int, int, int, int, Individual[], EvolutionState, int) - Method in class ec.gp.breed.MutatePromotePipeline
-
- produce(int, int, int, int, Individual[], EvolutionState, int) - Method in class ec.gp.breed.MutateSwapPipeline
-
- produce(int, int, int, int, Individual[], EvolutionState, int) - Method in class ec.gp.breed.RehangPipeline
-
- produce(int, int, int, int, Individual[], EvolutionState, int) - Method in class ec.gp.breed.SizeFairCrossoverPipeline
-
- produce(int, int, int, int, Individual[], EvolutionState, int) - Method in class ec.gp.koza.CrossoverPipeline
-
- produce(int, int, int, int, Individual[], EvolutionState, int) - Method in class ec.gp.koza.MutationPipeline
-
- produce(int, EvolutionState, int) - Method in class ec.parsimony.BucketTournamentSelection
-
- produce(int, EvolutionState, int) - Method in class ec.parsimony.DoubleTournamentSelection
-
Produces the index of a person selected from among several by a tournament.
- produce(int, EvolutionState, int) - Method in class ec.parsimony.RatioBucketTournamentSelection
-
- produce(int, int, int, int, Individual[], EvolutionState, int) - Method in class ec.rule.breed.RuleCrossoverPipeline
-
- produce(int, int, int, int, Individual[], EvolutionState, int) - Method in class ec.rule.breed.RuleMutationPipeline
-
- produce(int, EvolutionState, int) - Method in class ec.select.BestSelection
-
- produce(int, EvolutionState, int) - Method in class ec.select.FirstSelection
-
- produce(int, int, int, int, Individual[], EvolutionState, int) - Method in class ec.select.FirstSelection
-
- produce(int, EvolutionState, int) - Method in class ec.select.FitProportionateSelection
-
- produce(int, EvolutionState, int) - Method in class ec.select.GreedyOverselection
-
- produce(int, EvolutionState, int) - Method in class ec.select.MultiSelection
-
- produce(int, int, int, int, Individual[], EvolutionState, int) - Method in class ec.select.MultiSelection
-
- produce(int, EvolutionState, int) - Method in class ec.select.RandomSelection
-
- produce(int, int, int, int, Individual[], EvolutionState, int) - Method in class ec.select.RandomSelection
-
- produce(int, EvolutionState, int) - Method in class ec.select.SUSSelection
-
- produce(int, EvolutionState, int) - Method in class ec.select.TournamentSelection
-
- produce(int, int, int, int, Individual[], EvolutionState, int) - Method in class ec.SelectionMethod
-
- produce(int, EvolutionState, int) - Method in class ec.SelectionMethod
-
An alternative form of "produce" special to Selection Methods;
selects an individual from the given subpopulation and
returns its position in that subpopulation.
- produce(SelectionMethod, int, int, EvolutionState, int) - Method in class ec.spatial.SpatialMultiPopCoevolutionaryEvaluator
-
- produce(int, int, int, int, Individual[], EvolutionState, int) - Method in class ec.vector.breed.GeneDuplicationPipeline
-
- produce(int, int, int, int, Individual[], EvolutionState, int) - Method in class ec.vector.breed.ListCrossoverPipeline
-
- produce(int, int, int, int, Individual[], EvolutionState, int) - Method in class ec.vector.breed.MultipleVectorCrossoverPipeline
-
- produce(int, int, int, int, Individual[], EvolutionState, int) - Method in class ec.vector.breed.VectorCrossoverPipeline
-
- produce(int, int, int, int, Individual[], EvolutionState, int) - Method in class ec.vector.breed.VectorMutationPipeline
-
- produceCurrent(int, EvolutionState, int) - Method in class ec.coevolve.MultiPopCoevolutionaryEvaluator
-
Selects one individual from the given subpopulation.
- producePrevious(int, EvolutionState, int) - Method in class ec.coevolve.MultiPopCoevolutionaryEvaluator
-
Selects one individual from the previous subpopulation.
- produces(EvolutionState, Population, int, int) - Method in class ec.BreedingPipeline
-
- produces(EvolutionState, Population, int, int) - Method in class ec.BreedingSource
-
Returns true if this BreedingSource, when attached to the given
subpopulation, will produce individuals of the subpopulation's species.
- produces(EvolutionState, Population, int, int) - Method in class ec.gp.GPBreedingPipeline
-
Returns true if s is a GPSpecies.
- produces(EvolutionState, Population, int, int) - Method in class ec.select.MultiSelection
-
- produces(EvolutionState, Population, int, int) - Method in class ec.SelectionMethod
-
A default version of produces -- this method always returns
true under the assumption that the selection method works
with all Fitnesses.
- ProportionalTournamentSelection - Class in ec.parsimony
-
This selection method adds parsimony pressure to the regular tournament selection.
- ProportionalTournamentSelection() - Constructor for class ec.parsimony.ProportionalTournamentSelection
-
- Prototype - Interface in ec
-
Prototype classes typically have one or a few prototype instances
created during the course of a run.
- ps - Variable in class ec.eda.CMAESSpecies
-
The p_{\sigma} evolution path vector.
- PS_NONE - Static variable in class ec.util.ParameterDatabase
-
- PS_PRINT_PARAMS - Static variable in class ec.util.ParameterDatabase
-
- PS_UNKNOWN - Static variable in class ec.util.ParameterDatabase
-
- PSOBreeder - Class in ec.pso
-
PSOBreeder is a simple single-threaded Breeder which performs
Particle Swarm Optimization using the Particle class as individuals.
- PSOBreeder() - Constructor for class ec.pso.PSOBreeder
-
- PTC1 - Class in ec.gp.build
-
PTC1 implements the "Strongly-typed Probabilistic Tree Creation 1 (PTC1)" algorithm described in
- PTC1() - Constructor for class ec.gp.build.PTC1
-
- PTC2 - Class in ec.gp.build
-
PTC2 implements the "Strongly-typed Probabilistic Tree Creation 2 (PTC2)" algorithm described in
- PTC2() - Constructor for class ec.gp.build.PTC2
-
- PTCFunctionSet - Class in ec.gp.build
-
PTCFunctionSet is a GPFunctionSet which adheres to PTCFunctionSetForm, and thus
can be used with the PTC1 and PTC2 methods.
- PTCFunctionSet() - Constructor for class ec.gp.build.PTCFunctionSet
-
- PTCFunctionSetForm - Interface in ec.gp.build
-
PTCFunctionSetForm defines the methods that the PTC1 and PTC2 tree-creation
algorithms require of function sets.
- push(ADFContext) - Method in class ec.gp.ADFStack
-
Pushes an ADFContext onto the main stack.
- push(String) - Method in class ec.util.Parameter
-
Returns a new parameter with s added to the end of the current path items.
- push(String[]) - Method in class ec.util.Parameter
-
Returns a new parameter with the path items in s added to the end of the current path items.
- PushBuilder - Class in ec.gp.push
-
PushBuilder implements the Push-style tree building algorithm, which permits nonterminals of arbitrary arity.
- PushBuilder() - Constructor for class ec.gp.push.PushBuilder
-
- PushDefaults - Class in ec.gp.push
-
- PushDefaults() - Constructor for class ec.gp.push.PushDefaults
-
- PushInstruction - Class in ec.gp.push
-
PushInstruction encapsulates a custom Push instruction.
- PushInstruction() - Constructor for class ec.gp.push.PushInstruction
-
- pushOntoFloatStack(Interpreter, float) - Method in class ec.gp.push.PushProblem
-
Pushes a value onto the top of the float stack of the interpreter.
- pushOntoIntStack(Interpreter, int) - Method in class ec.gp.push.PushProblem
-
Pushes a value onto the top of the int stack of the interpreter.
- PushProblem - Class in ec.gp.push
-
A PushProblem contains useful methods to help you create an
interpreter, write out the ECJ GP tree to a string, build a Push Program
around this string, load the interpreter with all your custom instructions,
and run the Push Program on the interpreter.
- PushProblem() - Constructor for class ec.gp.push.PushProblem
-
- R_FAILURE - Static variable in class ec.EvolutionState
-
"The evolution run has quit, failing to find a perfect individual."
- R_NOTDONE - Static variable in class ec.EvolutionState
-
"The evolution run has not quit
- R_SUCCESS - Static variable in class ec.EvolutionState
-
"The evolution run has quit, finding a perfect individual."
- Rand1EitherOrDEBreeder - Class in ec.de
-
Rand1EitherOrDEBreeder is a differential evolution breeding operator.
- Rand1EitherOrDEBreeder() - Constructor for class ec.de.Rand1EitherOrDEBreeder
-
- random - Variable in class ec.EvolutionState
-
An array of random number generators, indexed by the thread number you were given (or, if you're not in a multithreaded area, use 0).
- RandomBranch - Class in ec.gp.build
-
RandomBranch implements the Random_Branch tree generation
method described in
- RandomBranch() - Constructor for class ec.gp.build.RandomBranch
-
- RandomChoice - Class in ec.util
-
RandomChoice organizes arrays of floats into distributions which can
be used to pick randomly from.
- RandomChoice() - Constructor for class ec.util.RandomChoice
-
- RandomChoiceChooser - Interface in ec.util
-
Used by RandomChoice to pick objects by probability from a distribution.
- RandomChoiceChooserD - Interface in ec.util
-
Used by RandomChoice to pick objects by probability from a distribution.
- randomizeOrder(EvolutionState, Individual[]) - Method in class ec.coevolve.CompetitiveEvaluator
-
- randomizeRulesOrder(EvolutionState, int) - Method in class ec.rule.RuleSet
-
Randomizes the order of the rules in the rule set.
- RandomRestarts - Class in ec.evolve
-
A special Statistics class which performs random restarts on the population,
effectively reininitializing the population and starting over again.
- RandomRestarts() - Constructor for class ec.evolve.RandomRestarts
-
- randomSeedOffset - Variable in class ec.EvolutionState
-
An amount to add to each random number generator seed to "offset" it -- often this is simply the job number.
- RandomSelection - Class in ec.select
-
Picks a random individual in the subpopulation.
- RandomSelection() - Constructor for class ec.select.RandomSelection
-
- randomValueFromClosedInterval(byte, byte, MersenneTwisterFast) - Method in class ec.vector.ByteVectorIndividual
-
Returns a random value from between min and max inclusive.
- randomValueFromClosedInterval(int, int, MersenneTwisterFast) - Method in class ec.vector.IntegerVectorIndividual
-
Returns a random value from between min and max inclusive.
- randomValueFromClosedInterval(long, long, MersenneTwisterFast) - Method in class ec.vector.LongVectorIndividual
-
Returns a random value from between min and max inclusive.
- randomValueFromClosedInterval(short, short, MersenneTwisterFast) - Method in class ec.vector.LongVectorIndividual
-
Returns a random value from between min and max inclusive.
- randomValueFromClosedInterval(short, short, MersenneTwisterFast) - Method in class ec.vector.ShortVectorIndividual
-
Returns a random value from between min and max inclusive.
- randomWalkProbability - Variable in class ec.vector.FloatVectorSpecies
-
The continuation probability for Integer Random Walk Mutation, per gene.
- randomWalkProbability(int) - Method in class ec.vector.FloatVectorSpecies
-
- randomWalkProbability - Variable in class ec.vector.IntegerVectorSpecies
-
The continuation probability for Integer Random Walk Mutation, per gene.
- randomWalkProbability(int) - Method in class ec.vector.IntegerVectorSpecies
-
- RandTree - Class in ec.gp.build
-
- RandTree() - Constructor for class ec.gp.build.RandTree
-
- RandTree.ArityObject - Class in ec.gp.build
-
- rank - Variable in class ec.multiobjective.nsga2.NSGA2MultiObjectiveFitness
-
Pareto front rank measure (lower ranks are better)
- ratio - Variable in class ec.parsimony.RatioBucketTournamentSelection
-
The value of RATIO
- RatioBucketTournamentSelection - Class in ec.parsimony
-
Does a tournament selection, limited to the subpopulation it's
working in at the time.
- RatioBucketTournamentSelection() - Constructor for class ec.parsimony.RatioBucketTournamentSelection
-
- rawFitness() - Method in class ec.gp.koza.KozaFitness
-
- readBooleanWithPreamble(String, EvolutionState, LineNumberReader) - Static method in class ec.util.Code
-
Finds the next nonblank line, skips past an expected preamble, and reads in a boolean value ("true" or "false") if there is one, and returns it.
- readByteWithPreamble(String, EvolutionState, LineNumberReader) - Static method in class ec.util.Code
-
Finds the next nonblank line, skips past an expected preamble, and reads in a byte if there is one, and returns it.
- readCharacterWithPreamble(String, EvolutionState, LineNumberReader) - Static method in class ec.util.Code
-
Finds the next nonblank line, skips past an expected preamble, and reads in a character if there is one, and returns it.
- readDoubleWithPreamble(String, EvolutionState, LineNumberReader) - Static method in class ec.util.Code
-
Finds the next nonblank line, skips past an expected preamble, and reads in a double if there is one, and returns it.
- readFitness(EvolutionState, LineNumberReader) - Method in class ec.Fitness
-
Reads in the fitness from a form outputted by fitnessToString() and thus
printFitnessForHumans(...).
- readFitness(EvolutionState, DataInput) - Method in class ec.Fitness
-
Reads the binary form of an individual from a DataInput.
- readFitness(EvolutionState, LineNumberReader) - Method in class ec.gp.koza.KozaFitness
-
- readFitness(EvolutionState, DataInput) - Method in class ec.gp.koza.KozaFitness
-
- readFitness(EvolutionState, LineNumberReader) - Method in class ec.multiobjective.MultiObjectiveFitness
-
- readFitness(EvolutionState, DataInput) - Method in class ec.multiobjective.MultiObjectiveFitness
-
- readFitness(EvolutionState, LineNumberReader) - Method in class ec.multiobjective.nsga2.NSGA2MultiObjectiveFitness
-
- readFitness(EvolutionState, DataInput) - Method in class ec.multiobjective.nsga2.NSGA2MultiObjectiveFitness
-
- readFitness(EvolutionState, LineNumberReader) - Method in class ec.multiobjective.spea2.SPEA2MultiObjectiveFitness
-
- readFitness(EvolutionState, DataInput) - Method in class ec.multiobjective.spea2.SPEA2MultiObjectiveFitness
-
- readFitness(EvolutionState, LineNumberReader) - Method in class ec.simple.SimpleFitness
-
Presently does not decode the fact that the fitness is ideal or not
- readFitness(EvolutionState, DataInput) - Method in class ec.simple.SimpleFitness
-
- readFloatWithPreamble(String, EvolutionState, LineNumberReader) - Static method in class ec.util.Code
-
Finds the next nonblank line, skips past an expected preamble, and reads in a float if there is one, and returns it.
- readGene(EvolutionState, LineNumberReader) - Method in class ec.vector.Gene
-
Reads a gene printed by printGene(...).
- readGene(EvolutionState, DataInput) - Method in class ec.vector.Gene
-
Override this if you need to read rules in from a binary stream
- readGeneFromString(String, EvolutionState) - Method in class ec.vector.Gene
-
Reads a gene from a string, which may contain a final '\n'.
- readGenotype(EvolutionState, DataInput) - Method in class ec.gp.GPIndividual
-
Overridden for the GPIndividual genotype.
- readGenotype(EvolutionState, DataInput) - Method in class ec.Individual
-
Reads in the genotypic information from a DataInput, erasing the previous genotype
of this Individual.
- readGenotype(EvolutionState, DataInput) - Method in class ec.rule.RuleIndividual
-
Overridden for the RuleIndividual genotype.
- readGenotype(EvolutionState, DataInput) - Method in class ec.vector.BitVectorIndividual
-
- readGenotype(EvolutionState, DataInput) - Method in class ec.vector.ByteVectorIndividual
-
- readGenotype(EvolutionState, DataInput) - Method in class ec.vector.DoubleVectorIndividual
-
- readGenotype(EvolutionState, DataInput) - Method in class ec.vector.FloatVectorIndividual
-
- readGenotype(EvolutionState, DataInput) - Method in class ec.vector.GeneVectorIndividual
-
- readGenotype(EvolutionState, DataInput) - Method in class ec.vector.IntegerVectorIndividual
-
- readGenotype(EvolutionState, DataInput) - Method in class ec.vector.LongVectorIndividual
-
- readGenotype(EvolutionState, DataInput) - Method in class ec.vector.ShortVectorIndividual
-
- readIndividual(EvolutionState, LineNumberReader) - Method in class ec.Individual
-
Reads in the individual from a form printed by printIndividual(), erasing the previous
information stored in this Individual.
- readIndividual(EvolutionState, DataInput) - Method in class ec.Individual
-
Reads the binary form of an individual from a DataInput, erasing the previous
information stored in this Individual.
- readIndividual(EvolutionState, LineNumberReader) - Method in class ec.pso.Particle
-
- readIndividual(EvolutionState, DataInput) - Method in class ec.pso.Particle
-
- readIntegerWithPreamble(String, EvolutionState, LineNumberReader) - Static method in class ec.util.Code
-
Finds the next nonblank line, skips past an expected preamble, and reads in an integer if there is one, and returns it.
- readLongWithPreamble(String, EvolutionState, LineNumberReader) - Static method in class ec.util.Code
-
Finds the next nonblank line, skips past an expected preamble, and reads in a long if there is one, and returns it.
- readNode(EvolutionState, DataInput) - Method in class ec.gp.ADF
-
- readNode(EvolutionState, DataInput) - Method in class ec.gp.ADFArgument
-
- readNode(EvolutionState, DataInput) - Method in class ec.gp.ERC
-
To successfully read from a DataOutput, you must override this to read your specific ERC data in.
- readNode(DecodeReturn) - Method in class ec.gp.ERC
-
- readNode(DecodeReturn) - Method in class ec.gp.GPNode
-
Reads the node symbol,
advancing the DecodeReturn to the first character in the string
beyond the node symbol, and returns a new, empty GPNode of the
appropriate class representing that symbol, else null if the
node symbol is not of the correct type for your GPNode class.
- readNode(EvolutionState, DataInput) - Method in class ec.gp.GPNode
-
Override this to read any additional node-specific information from dataInput besides: the number of arguments,
the specific node class, the children, and the parent.
- readPopulation(EvolutionState, LineNumberReader) - Method in class ec.Population
-
Reads a population from the format generated by printPopulation(....).
- readPopulation(EvolutionState, DataInput) - Method in class ec.Population
-
Reads a population in binary form, from the format generated by writePopulation(...).
- readRootedTree(EvolutionState, DataInput, GPType, GPFunctionSet, GPNodeParent, int) - Static method in class ec.gp.GPNode
-
- readRootedTree(int, DecodeReturn, GPType, GPFunctionSet, GPNodeParent, int, EvolutionState) - Static method in class ec.gp.GPNode
-
Reads the node and its children from the form printed out by printRootedTree.
- readRule(EvolutionState, LineNumberReader) - Method in class ec.rule.Rule
-
Reads a rule printed by printRule(...).
- readRule(EvolutionState, DataInput) - Method in class ec.rule.Rule
-
Override this if you need to read rules in from a binary stream
- readRuleFromString(String, EvolutionState) - Method in class ec.rule.Rule
-
Reads a rule from a string, which may contain a final '\n'.
- readRuleSet(EvolutionState, LineNumberReader) - Method in class ec.rule.RuleSet
-
Reads the rule set
- readRuleSet(EvolutionState, DataInput) - Method in class ec.rule.RuleSet
-
Reads RuleSets in from a binary stream
- readShortWithPreamble(String, EvolutionState, LineNumberReader) - Static method in class ec.util.Code
-
Finds the next nonblank line, skips past an expected preamble, and reads in a short if there is one, and returns it.
- readState(DataInputStream) - Method in class ec.util.MersenneTwister
-
Reads the entire state of the MersenneTwister RNG from the stream
- readState(DataInputStream) - Method in class ec.util.MersenneTwisterFast
-
Reads the entire state of the MersenneTwister RNG from the stream
- readStringWithPreamble(String, EvolutionState, LineNumberReader) - Static method in class ec.util.Code
-
Finds the next nonblank line, skips past an expected preamble, and reads in a string if there is one, and returns it.
- readSubpopulation(EvolutionState, LineNumberReader) - Method in class ec.Subpopulation
-
Reads a subpopulation from the format generated by printSubpopulation(....).
- readSubpopulation(EvolutionState, DataInput) - Method in class ec.Subpopulation
-
Reads a subpopulation in binary form, from the format generated by writeSubpopulation(...).
- readTree(EvolutionState, LineNumberReader) - Method in class ec.gp.GPTree
-
Reads in the tree from a form printed by printTree.
- readTree(EvolutionState, DataInput) - Method in class ec.gp.GPTree
-
- readTrials(EvolutionState, DataInput) - Method in class ec.Fitness
-
Reads trials in from DataInput.
- receiveAdditionalData(EvolutionState, DataInputStream) - Method in class ec.eval.MasterProblem
-
This method is called on a MasterProblem by the Slave.
- reduceBy - Variable in class ec.simple.SimpleBreeder
-
- reevaluateElites - Variable in class ec.simple.SimpleBreeder
-
- reevaluateIndividuals - Variable in class ec.eval.MetaProblem
-
Whether to reevaluate individuals if and when they appear for evaluation in the future.
- ReflectedObject - Class in ec.util
-
- ReflectedObject(Object) - Constructor for class ec.util.ReflectedObject
-
- ReflectedObject(Object, Class, String, Object) - Constructor for class ec.util.ReflectedObject
-
- registerSlave(EvolutionState, String, Socket, DataOutputStream, DataInputStream) - Method in class ec.eval.SlaveMonitor
-
Registers a new slave with the monitor.
- RehangPipeline - Class in ec.gp.breed
-
RehangPipeline picks a nonterminal node other than the root
and "rehangs" it as
a new root.
- RehangPipeline() - Constructor for class ec.gp.breed.RehangPipeline
-
- reinitializeContacts(EvolutionState) - Method in class ec.eval.MasterProblem
-
Reinitialize contacts with the slaves
- reinitializeContacts(EvolutionState) - Method in class ec.Evaluator
-
Called to reinitialize remote evaluation network contacts when the run is restarted from checkpoint.
- reinitializeContacts(EvolutionState) - Method in class ec.exchange.InterPopulationExchange
-
Initializes contacts with other processes, if that's what you're doing.
- reinitializeContacts(EvolutionState) - Method in class ec.exchange.IslandExchange
-
Initializes contacts with other processes, if that's what you're doing.
- reinitializeContacts(EvolutionState) - Method in class ec.Exchanger
-
Initializes contacts with other processes, if that's what you're doing.
- reinitializeContacts(EvolutionState) - Method in class ec.gp.ge.GEProblem
-
- reinitializeContacts(EvolutionState) - Method in class ec.Problem
-
Called to reinitialize remote evaluation network contacts when the run is restarted from checkpoint.
- reinitializeContacts(EvolutionState) - Method in class ec.simple.SimpleExchanger
-
Doesn't do anything.
- remove(Parameter) - Method in class ec.util.ParameterDatabase
-
Removes a parameter from the topmost database.
- removeDeeply(Parameter) - Method in class ec.util.ParameterDatabase
-
- removeLog(int) - Method in class ec.util.Output
-
Removes the given log.
- removeRandomRule(EvolutionState, int) - Method in class ec.rule.RuleSet
-
Removes a randomly-chosen rule from the rule set and returns it.
- removeRule(int) - Method in class ec.rule.RuleSet
-
Removes a rule from the rule set and returns it.
- removeTreeModelListener(TreeModelListener) - Method in class ec.util.ReflectedObject
-
- reopen() - Method in class ec.util.Log
-
Forces a file-based log to reopen, erasing its previous contents.
- reopen(Log) - Method in class ec.util.LogRestarter
-
- reopen(int) - Method in class ec.util.Output
-
Forces a file-based log to reopen, erasing its previous contents.
- reopen(int[]) - Method in class ec.util.Output
-
Forces one or more file-based logs to reopen, erasing
their previous contents.
- replacementProbability - Variable in class ec.steadystate.SteadyStateEvolutionState
-
When a new individual arrives, with what probability should it directly replace the existing
"marked for death" individual, as opposed to only replacing it if it's superior?
- replaceWith(GPNode) - Method in class ec.gp.GPNode
-
Replaces the node with another node in its position in the tree.
- repostAnnouncementsOnRestart - Variable in class ec.util.Log
-
Should the log repost all announcements on restart
- reproduce(int, int, int, Individual[], EvolutionState, int, boolean) - Method in class ec.BreedingPipeline
-
Performs direct cloning of n individuals.
- ReproductionPipeline - Class in ec.breed
-
ReproductionPipeline is a BreedingPipeline which simply makes a copy
of the individuals it recieves from its source.
- ReproductionPipeline() - Constructor for class ec.breed.ReproductionPipeline
-
- reserve - Variable in class ec.gp.ADFStack
-
- reset() - Method in class ec.gp.ADFStack
-
Pops off all items on the stack and the substack.
- reset() - Method in interface ec.gp.GPNodeSelector
-
Resets the Node Selector before a new series of pickNode()
if need be.
- reset() - Method in class ec.gp.koza.KozaNodeSelector
-
- reset(EvolutionState, int) - Method in class ec.pso.Particle
-
- reset(EvolutionState, int) - Method in class ec.rule.Rule
-
The reset method randomly reinitializes the rule.
- reset(EvolutionState, int) - Method in class ec.rule.RuleIndividual
-
- reset(EvolutionState, int) - Method in class ec.rule.RuleSet
-
A reset method for randomly reinitializing the RuleSet
- reset() - Method in class ec.util.DataPipe
-
Reset the buffer.
- reset(String) - Method in class ec.util.DecodeReturn
-
Use this to reuse your DecodeReturn for another string
- reset(String, int) - Method in class ec.util.DecodeReturn
-
Use this to reuse your DecodeReturn for another string
- reset(EvolutionState, int) - Method in class ec.vector.BitVectorIndividual
-
Initializes the individual by randomly flipping the bits
- reset(EvolutionState, int) - Method in class ec.vector.ByteVectorIndividual
-
Initializes the individual by randomly choosing Integers uniformly from mingene to maxgene.
- reset(EvolutionState, int) - Method in class ec.vector.DoubleVectorIndividual
-
Initializes the individual by randomly choosing doubles uniformly from
mingene to maxgene.
- reset(EvolutionState, int) - Method in class ec.vector.FloatVectorIndividual
-
Initializes the individual by randomly choosing floats uniformly from
mingene to maxgene.
- reset(EvolutionState, int) - Method in class ec.vector.Gene
-
The reset method randomly reinitializes the gene.
- reset(EvolutionState, int) - Method in class ec.vector.GeneVectorIndividual
-
Initializes the individual by calling reset(...) on each gene.
- reset(EvolutionState, int) - Method in class ec.vector.IntegerVectorIndividual
-
Initializes the individual by randomly choosing Integers uniformly from mingene to maxgene.
- reset(EvolutionState, int) - Method in class ec.vector.LongVectorIndividual
-
Initializes the individual by randomly choosing Longs uniformly from mingene to maxgene.
- reset(EvolutionState, int) - Method in class ec.vector.ShortVectorIndividual
-
Initializes the individual by randomly choosing Integers uniformly from mingene to maxgene.
- reset(EvolutionState, int) - Method in class ec.vector.VectorIndividual
-
Initializes the individual.
- reset(EvolutionState, int, int) - Method in class ec.vector.VectorIndividual
-
Initializes the individual to a new size.
- resetEachGeneration - Variable in class ec.breed.UniquePipeline
-
- resetFromCheckpoint() - Method in class ec.EvolutionState
-
This method is called after a checkpoint
is restored from but before the run starts up again.
- resetInterpreter(Interpreter) - Method in class ec.gp.push.PushProblem
-
Clears the Interpreter's stacks so it is ready to execute another program.
- resetMaxSize - Variable in class ec.rule.RuleSetConstraints
-
- resetMinSize - Variable in class ec.rule.RuleSetConstraints
-
- resetNode(EvolutionState, int) - Method in class ec.gp.ERC
-
Remember to override this to randomize your ERC after it has been cloned.
- resetNode(EvolutionState, int) - Method in class ec.gp.GPNode
-
Starts a node in a new life immediately after it has been cloned.
- resetNode(EvolutionState, int) - Method in class ec.gp.push.Terminal
-
- resize(int) - Method in class ec.Subpopulation
-
Resizes the Subpopulation to a new size.
- restart() - Method in class ec.util.Log
-
Restarts a log after a system restart from checkpoint.
- restart(Log) - Method in class ec.util.LogRestarter
-
- restart() - Method in class ec.util.Output
-
- restarter - Variable in class ec.util.Log
-
The log's restarter
- restoreFromCheckpoint(String) - Static method in class ec.util.Checkpoint
-
Returns an EvolutionState object read from a checkpoint file
whose filename is checkpoint
- retries - Variable in class ec.de.DEBreeder
-
- returntype - Variable in class ec.gp.GPNodeConstraints
-
The return type for a GPNode
- reverseMap(EvolutionState, GPIndividual, int) - Method in class ec.gp.ge.GESpecies
-
Reverse of the original map() function, takes a GPIndividual and returns
a corresponding GEIndividual; The GPIndividual may contain more than one trees,
and such cases are handled accordingly, see the 3rd bullet below --
NOTE:
This reverse mapping is only valid for S-expression trees ;
This procedure supports ERC for the current population (not for population
/subpopulation from other islands); However, that could be done by merging
all ERCBanks from all the sub-populations but that is not done yet ;
Support for the ADF's are done as follows -- suppose in one GPIndividual,
there are N trees -- T1, T2, ,,, Tn and each of them follows n different
grammars G1, G2, ,,, Gn respectively; now if they are reverse-mapped to
int arrays, there will be n int arrays A1[], A2[], ,,, An[]; and suppose
the i-th tree Ti is reverse mapped to int array Ai[] and morevoer Ai[] is
the longest among all the arrays (Bj[]s); so Bi[] is sufficient to build
all ADF trees Tjs.
- ROOT_D - Variable in class ec.gp.build.Uniform
-
- ROOT_D_ZERO - Variable in class ec.gp.build.Uniform
-
- rootedTreeEquals(GPNode) - Method in class ec.gp.GPNode
-
Returns true if the two rooted trees are "genetically" equal, though
they may have different parents.
- rootedTreeHashCode() - Method in class ec.gp.GPNode
-
Returns a hashcode associated with all the nodes in the tree.
- rootParent() - Method in class ec.gp.GPNode
-
Returns the root ancestor of this node.
- rootProbability - Variable in class ec.gp.koza.KozaNodeSelector
-
The probability the root must be chosen
- RPAREN - Static variable in class ec.gp.ge.GrammarParser
-
- RULE - Static variable in class ec.gp.ge.GrammarParser
-
- Rule - Class in ec.rule
-
Rule is an abstract class for describing rules.
- Rule() - Constructor for class ec.rule.Rule
-
- ruleConstraintRepository - Variable in class ec.rule.RuleInitializer
-
- RuleConstraints - Class in ec.rule
-
RuleConstraints is a class for constraints applicable to rules.
- RuleConstraints() - Constructor for class ec.rule.RuleConstraints
-
- ruleConstraints - Variable in class ec.rule.RuleInitializer
-
- RuleCrossoverPipeline - Class in ec.rule.breed
-
RuleCrossoverPipeline is a BreedingPipeline which implements a simple default crossover
for RuleIndividuals.
- RuleCrossoverPipeline() - Constructor for class ec.rule.breed.RuleCrossoverPipeline
-
- ruleCrossProbability - Variable in class ec.rule.breed.RuleCrossoverPipeline
-
What is the probability of a rule migrating?
- RuleDefaults - Class in ec.rule
-
A static class that returns the base for "default values" which rule-style
operators use, rather than making the user specify them all on a per-
species basis.
- RuleDefaults() - Constructor for class ec.rule.RuleDefaults
-
- RuleIndividual - Class in ec.rule
-
RuleIndividual is an Individual with an array of RuleSets, each of which
is a set of Rules.
- RuleIndividual() - Constructor for class ec.rule.RuleIndividual
-
- RuleInitializer - Class in ec.rule
-
A SimpleInitializer subclass designed to be used with rules.
- RuleInitializer() - Constructor for class ec.rule.RuleInitializer
-
- RuleMutationPipeline - Class in ec.rule.breed
-
RuleMutationPipeline is a BreedingPipeline which implements a simple default Mutation
for RuleIndividuals.
- RuleMutationPipeline() - Constructor for class ec.rule.breed.RuleMutationPipeline
-
- rulePrototype - Variable in class ec.rule.RuleSetConstraints
-
The prototype of the Rule that will be used in the RuleSet
(the RuleSet contains only rules with the specified prototype).
- rules - Variable in class ec.rule.RuleSet
-
The rules in the rule set
- RuleSet - Class in ec.rule
-
RuleSet is a set of Rules, implemented straightforwardly as an arbitrary-length array of Rules.
- RuleSet() - Constructor for class ec.rule.RuleSet
-
- ruleSetConstraintRepository - Variable in class ec.rule.RuleInitializer
-
- ruleSetConstraints - Variable in class ec.rule.RuleInitializer
-
- RuleSetConstraints - Class in ec.rule
-
RuleSetConstraints is an basic class for constraints applicable to rulesets.
- RuleSetConstraints() - Constructor for class ec.rule.RuleSetConstraints
-
- rulesets - Variable in class ec.rule.RuleIndividual
-
The individual's rulesets.
- RuleSpecies - Class in ec.rule
-
RuleSpecies is a simple individual which is suitable as a species
for rule sets subpopulations.
- RuleSpecies() - Constructor for class ec.rule.RuleSpecies
-
- run(int) - Method in class ec.EvolutionState
-
Starts the run.
- runComplete(EvolutionState) - Method in class ec.coevolve.CompetitiveEvaluator
-
- runComplete(EvolutionState) - Method in class ec.coevolve.MultiPopCoevolutionaryEvaluator
-
- runComplete - Variable in class ec.Evaluator
-
- runComplete(EvolutionState) - Method in class ec.Evaluator
-
Returns non-NULL if the Evaluator believes that the run is
finished: perhaps an ideal individual has been found or some
other run result has shortcircuited the run so that it should
end prematurely right now.
- runComplete(EvolutionState) - Method in class ec.exchange.InterPopulationExchange
-
Called after preBreedingExchangePopulation(...) to evaluate whether or not
the exchanger wishes the run to shut down (with ec.EvolutionState.R_FAILURE).
- runComplete(EvolutionState) - Method in class ec.exchange.IslandExchange
-
Called after preBreedingExchangePopulation(...) to evaluate whether or not
the exchanger wishes the run to shut down (with ec.EvolutionState.R_FAILURE).
- runComplete(EvolutionState) - Method in class ec.Exchanger
-
Called after preBreedingExchangePopulation(...) to evaluate whether or not
the exchanger wishes the run to shut down (with ec.EvolutionState.R_FAILURE) --
returns a String (which will be printed out as a message) if the exchanger
wants to shut down, else returns null if the exchanger does NOT want to shut down.
- runComplete(EvolutionState) - Method in class ec.simple.SimpleEvaluator
-
The SimpleEvaluator determines that a run is complete by asking
each individual in each population if he's optimal; if he
finds an individual somewhere that's optimal,
he signals that the run is complete.
- runComplete(EvolutionState) - Method in class ec.simple.SimpleExchanger
-
Always returns null
- runEvolve - Static variable in class ec.eval.Slave
-
- runs - Variable in class ec.eval.MetaProblem
-
The number of base-level evolutionary runs to perform to evaluate an individual.
- runTime - Static variable in class ec.eval.Slave
-
- runtimeArguments - Variable in class ec.EvolutionState
-
The original runtime arguments passed to the Java process.
- s - Variable in class ec.util.DecodeReturn
-
Stores strings, error messages
- sbd - Variable in class ec.eda.CMAESSpecies
-
bd x sigma
- scanAt(int) - Method in class ec.util.DecodeReturn
-
Sets the DecodeReturn to begin scanning at _pos, which should be valid.
- scheduleJobForEvaluation(EvolutionState, Job) - Method in class ec.eval.SlaveMonitor
-
Schedules a job for execution on one of the available slaves.
- SEED_INCREMENT - Static variable in class ec.eval.SlaveMonitor
-
- SelectDefaults - Class in ec.select
-
- SelectDefaults() - Constructor for class ec.select.SelectDefaults
-
- SelectionMethod - Class in ec
-
A SelectionMethod is a BreedingSource which provides direct IMMUTABLE pointers
to original individuals in an old population, not fresh mutable copies.
- SelectionMethod() - Constructor for class ec.SelectionMethod
-
- selects - Variable in class ec.select.MultiSelection
-
The MultiSelection's individuals
- sendAdditionalData(EvolutionState, DataOutputStream) - Method in class ec.eval.MasterProblem
-
This method is called from the SlaveMonitor's accept() thread to optionally send additional data to the
Slave via the dataOut stream.
- sequentialBreeding - Variable in class ec.simple.SimpleBreeder
-
- seriesCollection - Variable in class ec.display.chart.XYSeriesChartStatistics
-
- serverAddress - Variable in class ec.exchange.IslandExchange
-
The address of the server
- serverPort - Variable in class ec.exchange.IslandExchange
-
The port of the server
- serverThread - Variable in class ec.exchange.IslandExchange
-
The thread of the server (is different than null only for the island with the server)
- servSock - Variable in class ec.eval.SlaveMonitor
-
The socket where slaves connect.
- set - Variable in class ec.breed.UniquePipeline
-
- set(Parameter, String) - Method in class ec.util.ParameterDatabase
-
Sets a parameter in the topmost database to a given value, trimmed of
whitespace.
- SET - Static variable in class ec.util.ParameterDatabaseEvent
-
- setCheckpoint(EvolutionState) - Static method in class ec.util.Checkpoint
-
Writes the evolution state out to a file.
- setContext(Individual[], int) - Method in class ec.Fitness
-
- setContext(Individual[]) - Method in class ec.Fitness
-
- setFilePrefix(String) - Method in class ec.util.Output
-
- setFitness(EvolutionState, double) - Method in class ec.gp.koza.KozaFitness
-
Deprecated.
- setFitness(EvolutionState, double) - Method in class ec.simple.SimpleFitness
-
Deprecated.
- setFitness(EvolutionState, double, boolean) - Method in class ec.simple.SimpleFitness
-
- setFlush(boolean) - Method in class ec.util.Output
-
- setGenome(Object) - Method in class ec.pso.Particle
-
- setGenome(Object) - Method in class ec.vector.BitVectorIndividual
-
- setGenome(Object) - Method in class ec.vector.ByteVectorIndividual
-
- setGenome(Object) - Method in class ec.vector.DoubleVectorIndividual
-
- setGenome(Object) - Method in class ec.vector.FloatVectorIndividual
-
- setGenome(Object) - Method in class ec.vector.GeneVectorIndividual
-
- setGenome(Object) - Method in class ec.vector.IntegerVectorIndividual
-
- setGenome(Object) - Method in class ec.vector.LongVectorIndividual
-
- setGenome(Object) - Method in class ec.vector.ShortVectorIndividual
-
- setGenome(Object) - Method in class ec.vector.VectorIndividual
-
Sets the gene array.
- setGenomeLength(int) - Method in class ec.pso.Particle
-
- setGenomeLength(int) - Method in class ec.vector.BitVectorIndividual
-
- setGenomeLength(int) - Method in class ec.vector.ByteVectorIndividual
-
- setGenomeLength(int) - Method in class ec.vector.DoubleVectorIndividual
-
- setGenomeLength(int) - Method in class ec.vector.FloatVectorIndividual
-
- setGenomeLength(int) - Method in class ec.vector.GeneVectorIndividual
-
- setGenomeLength(int) - Method in class ec.vector.IntegerVectorIndividual
-
- setGenomeLength(int) - Method in class ec.vector.LongVectorIndividual
-
- setGenomeLength(int) - Method in class ec.vector.ShortVectorIndividual
-
- setGenomeLength(int) - Method in class ec.vector.VectorIndividual
-
Sets the genome length.
- setIndex(int, int) - Method in interface ec.spatial.Space
-
Input: a threadnumber (either for evaluation or for breeding), and an index in a subpopulation
(the index in the subpopulation is, of course, associated with a location in the space)
Functionality: stores the index and the threadnumber for further accesses to the getIndexRandomNeighbor
method.
- setIndex(int, int) - Method in class ec.spatial.Spatial1DSubpopulation
-
- setMinimumFitness(EvolutionState, int, Individual) - Method in class ec.parsimony.TarpeianStatistics
-
Sets the fitness of an individual to the minimum fitness possible.
- setObjectives(EvolutionState, double[]) - Method in class ec.multiobjective.MultiObjectiveFitness
-
- setProbability(Object, double) - Method in class ec.BreedingSource
-
- setProbability(Object, float) - Method in interface ec.util.RandomChoiceChooser
-
Sets obj's probability
- setProbability(Object, double) - Method in interface ec.util.RandomChoiceChooserD
-
Sets obj's probability
- setRunComplete(String) - Method in class ec.Evaluator
-
Requests that the Evaluator quit soon for a user-defined reason provided in the message.
- setSeed(String, int, int) - Method in class ec.display.ControlPanel
-
- setSeed(long) - Method in class ec.util.MersenneTwister
-
Initalize the pseudo random number generator.
- setSeed(int[]) - Method in class ec.util.MersenneTwister
-
Sets the seed of the MersenneTwister using an array of integers.
- setSeed(long) - Method in class ec.util.MersenneTwisterFast
-
Initalize the pseudo random number generator.
- setSeed(int[]) - Method in class ec.util.MersenneTwisterFast
-
Sets the seed of the MersenneTwister using an array of integers.
- setStandardizedFitness(EvolutionState, double) - Method in class ec.gp.koza.KozaFitness
-
Set the standardized fitness in the half-open interval [0.0,infinity)
which is defined (NOTE: DIFFERENT FROM fitness()!!!) as 0.0
being the IDEAL and infinity being worse than the worst possible.
- setStore(boolean) - Method in class ec.util.Output
-
Sets whether the Output stores its announcements.
- setThrowsErrors(boolean) - Method in class ec.util.Output
-
- setToBestOf(EvolutionState, Fitness[]) - Method in class ec.Fitness
-
Sets the fitness to be the same value as the best of the provided fitnesses.
- setToBestOf(EvolutionState, Fitness[]) - Method in class ec.multiobjective.MultiObjectiveFitness
-
- setToLambda(Population, EvolutionState) - Method in class ec.es.MuCommaLambdaBreeder
-
Sets all subpopulations in pop to the expected lambda size.
- setToMeanOf(EvolutionState, Fitness[]) - Method in class ec.Fitness
-
Sets the fitness to be the same value as the mean of the provided fitnesses.
- setToMeanOf(EvolutionState, Fitness[]) - Method in class ec.gp.koza.KozaFitness
-
- setToMeanOf(EvolutionState, Fitness[]) - Method in class ec.multiobjective.MultiObjectiveFitness
-
- setToMeanOf(EvolutionState, Fitness[]) - Method in class ec.simple.SimpleFitness
-
- setToMedianOf(EvolutionState, Fitness[]) - Method in class ec.Fitness
-
Sets the fitness to be the median of the provided fitnesses.
- setToMedianOf(EvolutionState, Fitness[]) - Method in class ec.multiobjective.MultiObjectiveFitness
-
- setToMuPlusLambda(Population, EvolutionState) - Method in class ec.es.MuPlusLambdaBreeder
-
Sets all subpopulations in pop to the expected mu+lambda size.
- setup(EvolutionState, Parameter) - Method in class ec.breed.BufferedBreedingPipeline
-
- setup(EvolutionState, Parameter) - Method in class ec.breed.CheckingPipeline
-
- setup(EvolutionState, Parameter) - Method in class ec.breed.ForceBreedingPipeline
-
- setup(EvolutionState, Parameter) - Method in class ec.breed.GenerationSwitchPipeline
-
- setup(EvolutionState, Parameter) - Method in class ec.breed.InitializationPipeline
-
- setup(EvolutionState, Parameter) - Method in class ec.breed.MultiBreedingPipeline
-
- setup(EvolutionState, Parameter) - Method in class ec.breed.ReproductionPipeline
-
- setup(EvolutionState, Parameter) - Method in class ec.breed.UniquePipeline
-
- setup(EvolutionState, Parameter) - Method in class ec.BreedingPipeline
-
- setup(EvolutionState, Parameter) - Method in class ec.BreedingSource
-
Sets up the BreedingPipeline.
- setup(EvolutionState, Parameter) - Method in class ec.coevolve.CompetitiveEvaluator
-
- setup(EvolutionState, Parameter) - Method in class ec.coevolve.MultiPopCoevolutionaryEvaluator
-
- setup(EvolutionState, Parameter) - Method in class ec.de.Best1BinDEBreeder
-
- setup(EvolutionState, Parameter) - Method in class ec.de.DEBreeder
-
- setup(EvolutionState, Parameter) - Method in class ec.de.Rand1EitherOrDEBreeder
-
- setup(EvolutionState, Parameter) - Method in class ec.display.chart.BarChartStatistics
-
- setup(EvolutionState, Parameter) - Method in class ec.display.chart.ChartableStatistics
-
- setup(EvolutionState, Parameter) - Method in class ec.display.chart.XYSeriesChartStatistics
-
- setup(EvolutionState, Parameter) - Method in class ec.display.portrayal.SimpleIndividualPortrayal
-
- setup(EvolutionState, Parameter) - Method in class ec.display.StatisticsChartPane
-
- setup(EvolutionState, Parameter) - Method in class ec.display.SubpopulationPanel
-
- setup(EvolutionState, Parameter) - Method in class ec.eda.CMAESBreeder
-
- setup(EvolutionState, Parameter) - Method in class ec.eda.CMAESSpecies
-
- setup(EvolutionState, Parameter) - Method in class ec.es.MuCommaLambdaBreeder
-
- setup(EvolutionState, Parameter) - Method in class ec.eval.MasterProblem
-
- setup(EvolutionState, Parameter) - Method in class ec.eval.MetaProblem
-
- setup(EvolutionState, Parameter) - Method in class ec.Evaluator
-
- setup(EvolutionState, Parameter) - Method in class ec.EvolutionState
-
Unlike for other setup() methods, ignore the base; it will always be null.
- setup(EvolutionState, Parameter) - Method in class ec.evolve.RandomRestarts
-
Gets the clock ticking.
- setup(EvolutionState, Parameter) - Method in class ec.exchange.InterPopulationExchange
-
- setup(EvolutionState, Parameter) - Method in class ec.exchange.IslandExchange
-
- setup(EvolutionState, Parameter) - Method in class ec.Fitness
-
- setup(EvolutionState, Parameter) - Method in class ec.gp.ADF
-
- setup(EvolutionState, Parameter) - Method in class ec.gp.ADFArgument
-
- setup(EvolutionState, Parameter) - Method in class ec.gp.ADFContext
-
- setup(EvolutionState, Parameter) - Method in class ec.gp.ADFStack
-
- setup(EvolutionState, Parameter) - Method in class ec.gp.breed.InternalCrossoverPipeline
-
- setup(EvolutionState, Parameter) - Method in class ec.gp.breed.MutateAllNodesPipeline
-
- setup(EvolutionState, Parameter) - Method in class ec.gp.breed.MutateDemotePipeline
-
- setup(EvolutionState, Parameter) - Method in class ec.gp.breed.MutateERCPipeline
-
- setup(EvolutionState, Parameter) - Method in class ec.gp.breed.MutateOneNodePipeline
-
- setup(EvolutionState, Parameter) - Method in class ec.gp.breed.MutatePromotePipeline
-
- setup(EvolutionState, Parameter) - Method in class ec.gp.breed.MutateSwapPipeline
-
- setup(EvolutionState, Parameter) - Method in class ec.gp.breed.RehangPipeline
-
- setup(EvolutionState, Parameter) - Method in class ec.gp.breed.SizeFairCrossoverPipeline
-
- setup(EvolutionState, Parameter) - Method in class ec.gp.build.PTC1
-
- setup(EvolutionState, Parameter) - Method in class ec.gp.build.PTC2
-
- setup(EvolutionState, Parameter) - Method in class ec.gp.build.PTCFunctionSet
-
- setup(EvolutionState, Parameter) - Method in class ec.gp.build.RandomBranch
-
- setup(EvolutionState, Parameter) - Method in class ec.gp.build.RandTree
-
- setup(EvolutionState, Parameter) - Method in class ec.gp.build.Uniform
-
- setup(EvolutionState, Parameter) - Method in class ec.gp.ge.GEProblem
-
- setup(EvolutionState, Parameter) - Method in class ec.gp.ge.GESpecies
-
- setup(EvolutionState, Parameter) - Method in class ec.gp.ge.GrammarParser
-
- setup(EvolutionState, Parameter) - Method in class ec.gp.GPData
-
- setup(EvolutionState, Parameter) - Method in class ec.gp.GPFunctionSet
-
Must be done after GPType and GPNodeConstraints have been set up
- setup(EvolutionState, Parameter) - Method in class ec.gp.GPIndividual
-
Sets up a prototypical GPIndividual with those features which it
shares with other GPIndividuals in its species, and nothing more.
- setup(EvolutionState, Parameter) - Method in class ec.gp.GPInitializer
-
- setup(EvolutionState, Parameter) - Method in class ec.gp.GPNode
-
Sets up a prototypical GPNode with those features all nodes of that
prototype share, and nothing more.
- setup(EvolutionState, Parameter) - Method in class ec.gp.GPNodeBuilder
-
- setup(EvolutionState, Parameter) - Method in class ec.gp.GPNodeConstraints
-
This must be called after the GPTypes have been set up.
- setup(EvolutionState, Parameter) - Method in class ec.gp.GPProblem
-
- setup(EvolutionState, Parameter) - Method in class ec.gp.GPSetType
-
- setup(EvolutionState, Parameter) - Method in class ec.gp.GPSpecies
-
- setup(EvolutionState, Parameter) - Method in class ec.gp.GPTree
-
Sets up a prototypical GPTree with those features it shares with
other GPTrees in its position in its GPIndividual, and nothhing more.
- setup(EvolutionState, Parameter) - Method in class ec.gp.GPTreeConstraints
-
This must be called after the GPTypes and GPFunctionSets
have been set up.
- setup(EvolutionState, Parameter) - Method in class ec.gp.GPType
-
- setup(EvolutionState, Parameter) - Method in class ec.gp.koza.CrossoverPipeline
-
- setup(EvolutionState, Parameter) - Method in class ec.gp.koza.HalfBuilder
-
- setup(EvolutionState, Parameter) - Method in class ec.gp.koza.KozaBuilder
-
- setup(EvolutionState, Parameter) - Method in class ec.gp.koza.KozaFitness
-
- setup(EvolutionState, Parameter) - Method in class ec.gp.koza.KozaNodeSelector
-
- setup(EvolutionState, Parameter) - Method in class ec.gp.koza.KozaShortStatistics
-
- setup(EvolutionState, Parameter) - Method in class ec.gp.koza.MutationPipeline
-
- setup(EvolutionState, Parameter) - Method in class ec.gp.push.PushBuilder
-
- setup(EvolutionState, Parameter) - Method in class ec.gp.push.PushInstruction
-
- setup(EvolutionState, Parameter) - Method in class ec.gp.push.Terminal
-
- setup(EvolutionState, Parameter) - Method in class ec.Individual
-
This should be used to set up only those things which you share in common
with all other individuals in your species; individual-specific items
which make you you should be filled in by Species.newIndividual(...),
and modified by breeders.
- setup(EvolutionState, Parameter) - Method in class ec.multiobjective.MultiObjectiveFitness
-
Sets up.
- setup(EvolutionState, Parameter) - Method in class ec.multiobjective.MultiObjectiveStatistics
-
- setup(EvolutionState, Parameter) - Method in class ec.multiobjective.nsga2.NSGA2Breeder
-
- setup(EvolutionState, Parameter) - Method in class ec.multiobjective.nsga2.NSGA2Evaluator
-
- setup(EvolutionState, Parameter) - Method in class ec.multiobjective.spea2.SPEA2Breeder
-
- setup(EvolutionState, Parameter) - Method in class ec.parsimony.BucketTournamentSelection
-
- setup(EvolutionState, Parameter) - Method in class ec.parsimony.DoubleTournamentSelection
-
- setup(EvolutionState, Parameter) - Method in class ec.parsimony.ProportionalTournamentSelection
-
- setup(EvolutionState, Parameter) - Method in class ec.parsimony.RatioBucketTournamentSelection
-
- setup(EvolutionState, Parameter) - Method in class ec.parsimony.TarpeianStatistics
-
- setup(EvolutionState, Parameter) - Method in class ec.Population
-
- setup(EvolutionState, Parameter) - Method in class ec.Problem
-
- setup(EvolutionState, Parameter) - Method in interface ec.Prototype
-
Sets up the object by reading it from the parameters stored
in state, built off of the parameter base base.
- setup(EvolutionState, Parameter) - Method in class ec.pso.Particle
-
- setup(EvolutionState, Parameter) - Method in class ec.pso.PSOBreeder
-
- setup(EvolutionState, Parameter) - Method in class ec.rule.breed.RuleCrossoverPipeline
-
- setup(EvolutionState, Parameter) - Method in class ec.rule.Rule
-
- setup(EvolutionState, Parameter) - Method in class ec.rule.RuleConstraints
-
- setup(EvolutionState, Parameter) - Method in class ec.rule.RuleIndividual
-
- setup(EvolutionState, Parameter) - Method in class ec.rule.RuleInitializer
-
Sets up the RuleConstraints and RuleSetConstraints cliques.
- setup(EvolutionState, Parameter) - Method in class ec.rule.RuleSet
-
- setup(EvolutionState, Parameter) - Method in class ec.rule.RuleSetConstraints
-
- setup(EvolutionState, Parameter) - Method in class ec.rule.RuleSpecies
-
- setup(EvolutionState, Parameter) - Method in class ec.select.BestSelection
-
- setup(EvolutionState, Parameter) - Method in class ec.select.BoltzmannSelection
-
- setup(EvolutionState, Parameter) - Method in class ec.select.GreedyOverselection
-
- setup(EvolutionState, Parameter) - Method in class ec.select.MultiSelection
-
- setup(EvolutionState, Parameter) - Method in class ec.select.SigmaScalingSelection
-
- setup(EvolutionState, Parameter) - Method in class ec.select.SUSSelection
-
- setup(EvolutionState, Parameter) - Method in class ec.select.TournamentSelection
-
- Setup - Interface in ec
-
Setup classes are classes which get set up once from user-supplied parameters
prior to being used.
- setup(EvolutionState, Parameter) - Method in interface ec.Setup
-
Sets up the object by reading it from the parameters stored
in state, built off of the parameter base base.
- setup(EvolutionState, Parameter) - Method in class ec.simple.SimpleBreeder
-
- setup(EvolutionState, Parameter) - Method in class ec.simple.SimpleEvaluator
-
- setup(EvolutionState, Parameter) - Method in class ec.simple.SimpleExchanger
-
- setup(EvolutionState, Parameter) - Method in class ec.simple.SimpleFinisher
-
- setup(EvolutionState, Parameter) - Method in class ec.simple.SimpleFitness
-
- setup(EvolutionState, Parameter) - Method in class ec.simple.SimpleInitializer
-
- setup(EvolutionState, Parameter) - Method in class ec.simple.SimpleShortStatistics
-
- setup(EvolutionState, Parameter) - Method in class ec.simple.SimpleStatistics
-
- setup(EvolutionState, Parameter) - Method in class ec.spatial.Spatial1DSubpopulation
-
Read additional parameters for the spatially-embedded subpopulation.
- setup(EvolutionState, Parameter) - Method in class ec.spatial.SpatialBreeder
-
- setup(EvolutionState, Parameter) - Method in class ec.spatial.SpatialTournamentSelection
-
- setup(EvolutionState, Parameter) - Method in class ec.Species
-
The default version of setup(...) loads requested pipelines and calls setup(...) on them and normalizes their probabilities.
- setup(EvolutionState, Parameter) - Method in class ec.Statistics
-
- setup(EvolutionState, Parameter) - Method in class ec.steadystate.SteadyStateBreeder
-
- setup(EvolutionState, Parameter) - Method in class ec.steadystate.SteadyStateEvaluator
-
- setup(EvolutionState, Parameter) - Method in class ec.steadystate.SteadyStateEvolutionState
-
- setup(EvolutionState, Parameter) - Method in class ec.Subpopulation
-
- setup(EvolutionState, Parameter) - Method in class ec.vector.BitVectorIndividual
-
- setup(EvolutionState, Parameter) - Method in class ec.vector.BitVectorSpecies
-
- setup(EvolutionState, Parameter) - Method in class ec.vector.breed.ListCrossoverPipeline
-
- setup(EvolutionState, Parameter) - Method in class ec.vector.breed.MultipleVectorCrossoverPipeline
-
- setup(EvolutionState, Parameter) - Method in class ec.vector.breed.VectorCrossoverPipeline
-
- setup(EvolutionState, Parameter) - Method in class ec.vector.ByteVectorIndividual
-
- setup(EvolutionState, Parameter) - Method in class ec.vector.DoubleVectorIndividual
-
- setup(EvolutionState, Parameter) - Method in class ec.vector.FloatVectorIndividual
-
- setup(EvolutionState, Parameter) - Method in class ec.vector.FloatVectorSpecies
-
- setup(EvolutionState, Parameter) - Method in class ec.vector.Gene
-
- setup(EvolutionState, Parameter) - Method in class ec.vector.GeneVectorIndividual
-
- setup(EvolutionState, Parameter) - Method in class ec.vector.GeneVectorSpecies
-
- setup(EvolutionState, Parameter) - Method in class ec.vector.IntegerVectorIndividual
-
- setup(EvolutionState, Parameter) - Method in class ec.vector.IntegerVectorSpecies
-
- setup(EvolutionState, Parameter) - Method in class ec.vector.LongVectorIndividual
-
- setup(EvolutionState, Parameter) - Method in class ec.vector.ShortVectorIndividual
-
- setup(EvolutionState, Parameter) - Method in class ec.vector.VectorSpecies
-
- setupArities(EvolutionState, GPFunctionSet) - Method in class ec.gp.build.RandTree
-
- setupConstraints(EvolutionState, Parameter) - Method in class ec.rule.RuleInitializer
-
Sets up all the RuleConstraints, loading them from the parameter
file.
- setupFunctionSets(EvolutionState, Parameter) - Method in class ec.gp.GPInitializer
-
- setupGenome(EvolutionState, Parameter) - Method in class ec.vector.VectorSpecies
-
- setupNodeConstraints(EvolutionState, Parameter) - Method in class ec.gp.GPInitializer
-
Sets up all the GPNodeConstraints, loading them from the parameter
file.
- setupPopulation(EvolutionState, int) - Method in class ec.eda.CMAESInitializer
-
- setupPopulation(EvolutionState, int) - Method in class ec.Initializer
-
Loads a Population from the parameter file, sets it up, and returns it.
- setupPopulation(EvolutionState, int) - Method in class ec.simple.SimpleInitializer
-
- setupProbabilities(BreedingSource[]) - Static method in class ec.BreedingSource
-
Normalizes and arranges the probabilities in sources so that they
are usable by pickRandom(...).
- setupRuleSetConstraints(EvolutionState, Parameter) - Method in class ec.rule.RuleInitializer
-
- setupTreeConstraints(EvolutionState, Parameter) - Method in class ec.gp.GPInitializer
-
Sets up all the GPTreeConstraints, loading them from the parameter
file.
- setupTypes(EvolutionState, Parameter) - Method in class ec.gp.GPInitializer
-
Sets up all the types, loading them from the parameter file.
- setVerbosity(int) - Method in class ec.util.Output
-
- setVisibleLeaves(boolean) - Method in class ec.util.ParameterDatabaseTreeModel
-
- ShortVectorIndividual - Class in ec.vector
-
ShortVectorIndividual is a VectorIndividual whose genome is an array of shorts.
- ShortVectorIndividual() - Constructor for class ec.vector.ShortVectorIndividual
-
- shouldBreedSubpop(EvolutionState, int, int) - Method in class ec.simple.SimpleBreeder
-
Returns true if we're doing sequential breeding and it's the subpopulation's turn (round robin,
one subpopulation per generation).
- shouldEvaluateSubpop(EvolutionState, int, int) - Method in class ec.coevolve.MultiPopCoevolutionaryEvaluator
-
Returns true if the subpopulation should be evaluated.
- shuffle(EvolutionState, int[]) - Method in class ec.coevolve.MultiPopCoevolutionaryEvaluator
-
- shuffle(GPNode[], EvolutionState, int) - Method in class ec.gp.push.PushBuilder
-
- shuffle - Variable in class ec.select.SUSSelection
-
Should we shuffle first?
- shutdown() - Method in class ec.eval.SlaveMonitor
-
Shuts down the slave monitor (also shuts down all slaves).
- sigma - Variable in class ec.eda.CMAESSpecies
-
The "sigma" scaling factor for the covariance matrix.
- SigmaScalingSelection - Class in ec.select
-
Similar to FitProportionateSelection, but with adjustments to scale up/exaggerate differences in fitness for selection when true fitness values are very close to
eachother across the population.
- SigmaScalingSelection() - Constructor for class ec.select.SigmaScalingSelection
-
- silent - Variable in class ec.util.Log
-
Should we write to this log at all?
- silentFile - Variable in class ec.Statistics
-
- silentFront - Variable in class ec.multiobjective.MultiObjectiveStatistics
-
- silentPrint - Variable in class ec.Statistics
-
- SimpleBreeder - Class in ec.simple
-
Breeds each subpopulation separately, with no inter-population exchange,
and using a generational approach.
- SimpleBreeder() - Constructor for class ec.simple.SimpleBreeder
-
- SimpleDefaults - Class in ec.simple
-
- SimpleDefaults() - Constructor for class ec.simple.SimpleDefaults
-
- SimpleEvaluator - Class in ec.simple
-
The SimpleEvaluator is a simple, non-coevolved generational evaluator which
evaluates every single member of every subpopulation individually in its
own problem space.
- SimpleEvaluator() - Constructor for class ec.simple.SimpleEvaluator
-
- SimpleEvolutionState - Class in ec.simple
-
A SimpleEvolutionState is an EvolutionState which implements a simple form
of generational evolution.
- SimpleEvolutionState() - Constructor for class ec.simple.SimpleEvolutionState
-
- SimpleExchanger - Class in ec.simple
-
A SimpleExchanger is a default Exchanger which, well, doesn't do anything.
- SimpleExchanger() - Constructor for class ec.simple.SimpleExchanger
-
- SimpleFinisher - Class in ec.simple
-
SimpleFinisher is a default Finisher which doesn't do anything.
- SimpleFinisher() - Constructor for class ec.simple.SimpleFinisher
-
- SimpleFitness - Class in ec.simple
-
A simple default fitness, consisting of a double floating-point value
where fitness A is superior to fitness B if and only if A > B.
- SimpleFitness() - Constructor for class ec.simple.SimpleFitness
-
- SimpleIndividualPortrayal - Class in ec.display.portrayal
-
This portrayal uses a text pane to display the results of
printIndividualForHumans()
.
- SimpleIndividualPortrayal() - Constructor for class ec.display.portrayal.SimpleIndividualPortrayal
-
- SimpleInitializer - Class in ec.simple
-
SimpleInitializer is a default Initializer which initializes a Population
by calling the Population's populate(...) method.
- SimpleInitializer() - Constructor for class ec.simple.SimpleInitializer
-
- SimpleProblemForm - Interface in ec.simple
-
SimpleProblemForm is an interface which defines methods
for Problems to implement simple, single-individual (non-coevolutionary)
evaluation.
- SimpleShortStatistics - Class in ec.simple
-
A Simple-style statistics generator, intended to be easily parseable with
awk or other Unix tools.
- SimpleShortStatistics() - Constructor for class ec.simple.SimpleShortStatistics
-
- SimpleStatistics - Class in ec.simple
-
A basic Statistics class suitable for simple problem applications.
- SimpleStatistics() - Constructor for class ec.simple.SimpleStatistics
-
- simulatedBinaryCrossover(MersenneTwisterFast, DoubleVectorIndividual, double) - Method in class ec.vector.DoubleVectorIndividual
-
- simulatedBinaryCrossover(MersenneTwisterFast, FloatVectorIndividual, float) - Method in class ec.vector.FloatVectorIndividual
-
- Singleton - Interface in ec
-
A Singleton is a class for which there will be only one instance
in the entire course of a run, and which will exist for pretty
much the entire run.
- size - Variable in class ec.exchange.IslandExchange
-
how many individuals to send each time
- size() - Method in class ec.gp.GPIndividual
-
Returns the "size" of the individual, namely, the number of nodes
in all of its subtrees.
- size() - Method in class ec.Individual
-
Returns the "size" of the individual.
- size - Variable in class ec.parsimony.BucketTournamentSelection
-
Size of the tournament
- size - Variable in class ec.parsimony.DoubleTournamentSelection
-
Size of the tournament
- size - Variable in class ec.parsimony.RatioBucketTournamentSelection
-
Size of the tournament
- size() - Method in class ec.rule.RuleIndividual
-
- size - Variable in class ec.select.BestSelection
-
Base size of the tournament; this may change.
- size() - Method in class ec.util.DataPipe
-
Returns the total size of the buffer.
- size() - Method in class ec.vector.VectorIndividual
-
- size2 - Variable in class ec.parsimony.DoubleTournamentSelection
-
- SIZE_OF_BYTE - Static variable in class ec.gp.GPInitializer
-
- SIZE_OF_BYTE - Static variable in class ec.gp.GPNodeConstraints
-
- SIZE_OF_BYTE - Static variable in class ec.gp.GPTreeConstraints
-
- SIZE_OF_BYTE - Static variable in class ec.rule.RuleInitializer
-
- sizeDistribution - Variable in class ec.gp.GPNodeBuilder
-
the maximum possible size -- if unused, it's 0
- sizeDistribution - Variable in class ec.rule.RuleSetConstraints
-
- SizeFairCrossoverPipeline - Class in ec.gp.breed
-
SizeFairCrossover works similarly to one written in the paper
"Size Fair and Homologous Tree Genetic Programming Crossovers" by Langdon (1998).
- SizeFairCrossoverPipeline() - Constructor for class ec.gp.breed.SizeFairCrossoverPipeline
-
- Slave - Class in ec.eval
-
Slave.java
- Slave() - Constructor for class ec.eval.Slave
-
- SlaveMonitor - Class in ec.eval
-
SlaveMonitor.java
- SlaveMonitor(EvolutionState, boolean, MasterProblem) - Constructor for class ec.eval.SlaveMonitor
-
Simple constructor that initializes the data structures for keeping track of the state of each slave.
- slaveNum - Static variable in class ec.eval.Slave
-
My unique slave number.
- SLEEP_TIME - Static variable in class ec.eval.Slave
-
How long we sleep in between attempts to connect to the master (in milliseconds).
- SLEEP_TIME - Static variable in class ec.exchange.IslandExchange
-
How long we sleep in between attempts to connect or look for signals
- sort(Object, Comparator) - Method in class ec.util.ParameterDatabaseTreeModel
-
- SortComparator - Interface in ec.util
-
The interface for passing objects to ec.util.QuickSort
- SortComparatorL - Interface in ec.util
-
The interface for passing objects to ec.util.QuickSort
- sortedFitOver - Variable in class ec.select.GreedyOverselection
-
- sortedFitUnder - Variable in class ec.select.GreedyOverselection
-
- sortedPop - Variable in class ec.select.BestSelection
-
Sorted, normalized, totalized fitnesses for the population
- sortedPop - Variable in class ec.select.GreedyOverselection
-
Sorted population -- since I *have* to use an int-sized
individual (short gives me only 16K),
I might as well just have pointers to the
population itself.
- sources - Variable in class ec.BreedingPipeline
-
Array of sources feeding the pipeline
- sourcesAreProperForm(SteadyStateEvolutionState) - Method in class ec.BreedingPipeline
-
- sourcesAreProperForm(SteadyStateEvolutionState) - Method in class ec.parsimony.BucketTournamentSelection
-
- sourcesAreProperForm(SteadyStateEvolutionState) - Method in class ec.parsimony.DoubleTournamentSelection
-
- sourcesAreProperForm(SteadyStateEvolutionState) - Method in class ec.parsimony.RatioBucketTournamentSelection
-
- sourcesAreProperForm(SteadyStateEvolutionState) - Method in class ec.select.FirstSelection
-
- sourcesAreProperForm(SteadyStateEvolutionState) - Method in class ec.select.RandomSelection
-
- sourcesAreProperForm(SteadyStateEvolutionState) - Method in class ec.select.TournamentSelection
-
- sourcesAreProperForm(SteadyStateEvolutionState, BreedingPipeline[]) - Method in class ec.steadystate.SteadyStateBreeder
-
Called to check to see if the breeding sources are correct -- if you
use this method, you must call state.output.exitIfErrors() immediately
afterwards.
- sourcesAreProperForm(SteadyStateEvolutionState) - Method in interface ec.steadystate.SteadyStateBSourceForm
-
Issue an error (not a fatal -- we guarantee that callers
of this method will also call exitIfErrors) if any
of your sources, or their sources, etc., are not
of SteadyStateBSourceForm.
- Space - Interface in ec.spatial
-
In a spatially-embedded EA, the subpopulations of individuals are assumed to be
spatially distributed in some sort of space, be it one-dimmensional, two-
dimmensional, or whatever else.
- sparsity - Variable in class ec.multiobjective.nsga2.NSGA2MultiObjectiveFitness
-
Sparsity along front rank measure (higher sparsity is better)
- Spatial1DSubpopulation - Class in ec.spatial
-
A Spatial1DSubpopulation is an EC subpopulation that is additionally embedded into
a one-dimmensional space.
- Spatial1DSubpopulation() - Constructor for class ec.spatial.Spatial1DSubpopulation
-
- SpatialBreeder - Class in ec.spatial
-
A slight modification of the simple breeder for spatially-embedded EAs.
- SpatialBreeder() - Constructor for class ec.spatial.SpatialBreeder
-
- SpatialDefaults - Class in ec.spatial
-
- SpatialDefaults() - Constructor for class ec.spatial.SpatialDefaults
-
- SpatialMultiPopCoevolutionaryEvaluator - Class in ec.spatial
-
SpatialMultiPopCoevolutionaryEvaluator implements a coevolutionary evaluator involving multiple
spatially-embedded subpopulations.
- SpatialMultiPopCoevolutionaryEvaluator() - Constructor for class ec.spatial.SpatialMultiPopCoevolutionaryEvaluator
-
- SpatialTournamentSelection - Class in ec.spatial
-
A slight modification of the tournament selection procedure for use with spatially-embedded EAs.
- SpatialTournamentSelection() - Constructor for class ec.spatial.SpatialTournamentSelection
-
- SPEA2_DISTANCE_PREAMBLE - Static variable in class ec.multiobjective.spea2.SPEA2MultiObjectiveFitness
-
- SPEA2_FITNESS_PREAMBLE - Static variable in class ec.multiobjective.spea2.SPEA2MultiObjectiveFitness
-
- SPEA2_STRENGTH_PREAMBLE - Static variable in class ec.multiobjective.spea2.SPEA2MultiObjectiveFitness
-
- SPEA2Breeder - Class in ec.multiobjective.spea2
-
This subclass of SimpleBreeder overrides the loadElites method to build an archive in the top elites[subpopnum]
of each subpopulation.
- SPEA2Breeder() - Constructor for class ec.multiobjective.spea2.SPEA2Breeder
-
- SPEA2Evaluator - Class in ec.multiobjective.spea2
-
This subclass of SimpleEvaluator evaluates the population, then computes auxiliary fitness
data of each subpopulation.
- SPEA2Evaluator() - Constructor for class ec.multiobjective.spea2.SPEA2Evaluator
-
- SPEA2MultiObjectiveFitness - Class in ec.multiobjective.spea2
-
SPEA2MultiObjectiveFitness is a subclass of MultiObjectiveFitness which adds three auxiliary fitness
measures used in SPEA2: strength S(i), kthNNDistance D(i), and a final fitness value R(i) + D(i).
- SPEA2MultiObjectiveFitness() - Constructor for class ec.multiobjective.spea2.SPEA2MultiObjectiveFitness
-
- SPEA2TournamentSelection - Class in ec.multiobjective.spea2
-
This is a special version of TournamentSelection which restricts the selection to only
the archive region (the top 'archiveSize' elements in the subpopulation).
- SPEA2TournamentSelection() - Constructor for class ec.multiobjective.spea2.SPEA2TournamentSelection
-
- species - Variable in class ec.Individual
-
The species of the Individual.
- Species - Class in ec
-
Species is a prototype which defines the features for a set of individuals
in the population.
- Species() - Constructor for class ec.Species
-
- species - Variable in class ec.Subpopulation
-
The species for individuals in this subpopulation.
- split(int[], RuleSet[]) - Method in class ec.rule.RuleSet
-
Splits the rule set into n pieces, according to points, which *must* be sorted.
- split(EvolutionState, int, RuleSet[]) - Method in class ec.rule.RuleSet
-
Splits the rule set into a number of disjoint rule sets, copying the rules and adding
them to the sets as appropriate.
- split(int[], Object[]) - Method in class ec.vector.BitVectorIndividual
-
Splits the genome into n pieces, according to points, which *must* be sorted.
- split(int[], Object[]) - Method in class ec.vector.ByteVectorIndividual
-
Splits the genome into n pieces, according to points, which *must* be sorted.
- split(int[], Object[]) - Method in class ec.vector.DoubleVectorIndividual
-
Splits the genome into n pieces, according to points, which *must* be
sorted.
- split(int[], Object[]) - Method in class ec.vector.FloatVectorIndividual
-
Splits the genome into n pieces, according to points, which *must* be
sorted.
- split(int[], Object[]) - Method in class ec.vector.GeneVectorIndividual
-
Splits the genome into n pieces, according to points, which *must* be sorted.
- split(int[], Object[]) - Method in class ec.vector.IntegerVectorIndividual
-
Splits the genome into n pieces, according to points, which *must* be sorted.
- split(int[], Object[]) - Method in class ec.vector.LongVectorIndividual
-
Splits the genome into n pieces, according to points, which *must* be sorted.
- split(int[], Object[]) - Method in class ec.vector.ShortVectorIndividual
-
Splits the genome into n pieces, according to points, which *must* be sorted.
- split(int[], Object[]) - Method in class ec.vector.VectorIndividual
-
Splits the genome into n pieces, according to points, which *must* be sorted.
- splitIntoTwo(EvolutionState, int, RuleSet[], double) - Method in class ec.rule.RuleSet
-
Splits the rule set into a two disjoint rule sets, copying the rules and adding
them to the sets as appropriate.
- stack - Variable in class ec.gp.ADFStack
-
- stack - Variable in class ec.gp.GPProblem
-
The GPProblem's stack
- standardizedFitness - Variable in class ec.gp.koza.KozaFitness
-
This ranges from 0 (best) to infinity (worst).
- standardizedFitness() - Method in class ec.gp.koza.KozaFitness
-
Returns the standardized fitness metric.
- start - Variable in class ec.evolve.RandomRestarts
-
- start(Runnable) - Method in class ec.util.ThreadPool
-
Start a thread on the given Runnable and returns it.
- start(Runnable, String) - Method in class ec.util.ThreadPool
-
Start a thread on the given Runnable with a given thread name (for debugging purposes).
- start(Runnable, int) - Method in class ec.util.ThreadPool
-
Start a thread on the given Runnable and returns it.
- start(Runnable, int, String) - Method in class ec.util.ThreadPool
-
Start a thread on the given Runnable with a given thread name
(for debugging purposes) and returns it.
- startFresh() - Method in class ec.EvolutionState
-
- startFresh() - Method in class ec.exchange.IslandExchange
-
- startFresh() - Method in class ec.simple.SimpleEvolutionState
-
- startFresh() - Method in class ec.steadystate.SteadyStateEvolutionState
-
- startFromCheckpoint() - Method in class ec.EvolutionState
-
- startFromCheckpoint() - Method in class ec.exchange.IslandExchange
-
- state - Variable in class ec.eval.SlaveMonitor
-
- stateEquals(MersenneTwister) - Method in class ec.util.MersenneTwister
-
Returns true if the MersenneTwister's current internal state is equal to another MersenneTwister.
- stateEquals(MersenneTwisterFast) - Method in class ec.util.MersenneTwisterFast
-
Returns true if the MersenneTwisterFast's current internal state is equal to another MersenneTwisterFast.
- statistics - Variable in class ec.EvolutionState
-
The population statistics, a singleton object.
- Statistics - Class in ec
-
Statistics and its subclasses are Cliques which generate statistics
during the run.
- Statistics() - Constructor for class ec.Statistics
-
- StatisticsChartPane - Class in ec.display
-
- StatisticsChartPane() - Constructor for class ec.display.StatisticsChartPane
-
- StatisticsChartPane(int) - Constructor for class ec.display.StatisticsChartPane
-
- StatisticsChartPane(int, int) - Constructor for class ec.display.StatisticsChartPane
-
- StatisticsChartPaneTab - Class in ec.display.chart
-
- StatisticsChartPaneTab(ChartPanel) - Constructor for class ec.display.chart.StatisticsChartPaneTab
-
- StatisticsChartPaneTab(ChartPanel, boolean) - Constructor for class ec.display.chart.StatisticsChartPaneTab
-
- statisticslog - Variable in class ec.simple.SimpleShortStatistics
-
- statisticslog - Variable in class ec.simple.SimpleStatistics
-
The Statistics' log
- SteadyStateBreeder - Class in ec.steadystate
-
This subclass of Breeder performs the evaluation portion of Steady-State Evolution and (in distributed form)
Asynchronous Evolution.
- SteadyStateBreeder() - Constructor for class ec.steadystate.SteadyStateBreeder
-
Do we allow duplicates?
- SteadyStateBSourceForm - Interface in ec.steadystate
-
- SteadyStateDefaults - Class in ec.steadystate
-
- SteadyStateDefaults() - Constructor for class ec.steadystate.SteadyStateDefaults
-
- SteadyStateEvaluator - Class in ec.steadystate
-
This subclass of Evaluator performs the evaluation portion of Steady-State Evolution and (in distributed form)
Asynchronous Evolution.
- SteadyStateEvaluator() - Constructor for class ec.steadystate.SteadyStateEvaluator
-
- SteadyStateEvolutionState - Class in ec.steadystate
-
This subclass of EvolutionState implements basic Steady-State Evolution and (in distributed form)
Asynchronous Evolution.
- SteadyStateEvolutionState() - Constructor for class ec.steadystate.SteadyStateEvolutionState
-
- SteadyStateExchangerForm - Interface in ec.steadystate
-
The SteadyStateExchangerForm is a badge which Exchanger subclasses
may wear if they work properly with the SteadyStateEvolutionState
mechanism.
- SteadyStateStatisticsForm - Interface in ec.steadystate
-
This interface defines the hooks for SteadyStateEvolutionState objects
to update themselves on.
- steps - Variable in class ec.select.SUSSelection
-
How many samples have been done?
- strength - Variable in class ec.multiobjective.spea2.SPEA2MultiObjectiveFitness
-
SPEA2 strength (# of nodes it dominates)
- STRING_CONSTANT - Static variable in class ec.gp.ge.GrammarParser
-
- style - Variable in class ec.coevolve.CompetitiveEvaluator
-
- STYLE_N_RANDOM_COMPETITORS_ONEWAY - Static variable in class ec.coevolve.CompetitiveEvaluator
-
- STYLE_N_RANDOM_COMPETITORS_TWOWAY - Static variable in class ec.coevolve.CompetitiveEvaluator
-
- STYLE_ROUND_ROBIN - Static variable in class ec.coevolve.CompetitiveEvaluator
-
- STYLE_SINGLE_ELIMINATION - Static variable in class ec.coevolve.CompetitiveEvaluator
-
- subpop - Variable in class ec.steadystate.QueueIndividual
-
- SUBPOP_INDEX_PREAMBLE - Static variable in class ec.Population
-
- subpops - Variable in class ec.Population
-
- Subpopulation - Class in ec
-
Subpopulation is a group which is basically an array of Individuals.
- Subpopulation() - Constructor for class ec.Subpopulation
-
- SubpopulationPanel - Class in ec.display
-
- SubpopulationPanel(Console, int) - Constructor for class ec.display.SubpopulationPanel
-
- SubpopulationPanel(Console, int, boolean) - Constructor for class ec.display.SubpopulationPanel
-
- substack - Variable in class ec.gp.ADFStack
-
- sumSquaredObjectiveDistance(MultiObjectiveFitness) - Method in class ec.multiobjective.MultiObjectiveFitness
-
Returns the sum of the squared difference between two Fitnesses in Objective space.
- SUSSelection - Class in ec.select
-
Picks individuals in a population using the Stochastic Universal Selection (SUS) process, using
fitnesses as returned by their fitness() methods.
- SUSSelection() - Constructor for class ec.select.SUSSelection
-
- swapCompatibleWith(GPInitializer, GPNode) - Method in class ec.gp.GPNode
-
Returns true if I can swap into node's position.
- SYNC - Static variable in class ec.exchange.IslandExchange
-
Synchronize signal
- synchronous - Variable in class ec.exchange.IslandExchange
-
synchronous or asynchronous communication
- systemMessage(String) - Method in class ec.util.Output
-
Posts a system message.
- T_BOOLEAN - Static variable in class ec.util.DecodeReturn
-
- T_BYTE - Static variable in class ec.util.DecodeReturn
-
- T_CHAR - Static variable in class ec.util.DecodeReturn
-
- T_CHARACTER - Static variable in class ec.util.DecodeReturn
-
Same as T_CHAR
- T_DOUBLE - Static variable in class ec.util.DecodeReturn
-
- T_ERROR - Static variable in class ec.util.DecodeReturn
-
The actual error is stored in the String slot
- T_FLOAT - Static variable in class ec.util.DecodeReturn
-
- T_INT - Static variable in class ec.util.DecodeReturn
-
- T_INTEGER - Static variable in class ec.util.DecodeReturn
-
Same as T_INT
- T_LONG - Static variable in class ec.util.DecodeReturn
-
- T_SHORT - Static variable in class ec.util.DecodeReturn
-
- T_STRING - Static variable in class ec.util.DecodeReturn
-
- TarpeianStatistics - Class in ec.parsimony
-
This Statistics subclass implements Poli's "Tarpeian" method of parsimony control, whereby some
kill-proportion of above-average-sized individuals in each subpopulation have their fitnesses
set to a very bad value, and marks them as already evaluated (so the Evaluator can skip them).
- TarpeianStatistics() - Constructor for class ec.parsimony.TarpeianStatistics
-
- Terminal - Class in ec.gp.push
-
Terminal is the leaf node in Push trees and is used to represent Push
instructions of all types.
- Terminal() - Constructor for class ec.gp.push.Terminal
-
- terminalProbabilities(int) - Method in class ec.gp.build.PTCFunctionSet
-
- terminalProbabilities(int) - Method in interface ec.gp.build.PTCFunctionSetForm
-
Returns an organized distribution (see ec.util.RandomChoice) of likelihoods
that various terminals in the function set will be chosen over other terminals
with the same return type.
- terminalProbability - Variable in class ec.gp.koza.KozaNodeSelector
-
The probability a terminal must be chosen
- terminals - Variable in class ec.gp.GPFunctionSet
-
The terminals our GPTree can use: terminals[type][thenodes].
- terminals - Variable in class ec.gp.koza.KozaNodeSelector
-
The number of terminals in the tree, -1 if unknown.
- terminals_h - Variable in class ec.gp.GPFunctionSet
-
The terminals our GPTree can use: arrays of terminals hashed by type.
- test(GPNode) - Method in class ec.gp.GPNodeGatherer
-
Returns true if thisNode is the kind of node to be considered in the
gather count for nodeInPosition(...) and GPNode.numNodes(GPNodeGatherer).
- ThreadPool - Class in ec.util
-
ThreadPool.java
A simple, lightweight thread pool, for those who cannot or will not use Java's baroque
java.util.concurrent package.
- ThreadPool() - Constructor for class ec.util.ThreadPool
-
- ThreadPool.Worker - Interface in ec.util
-
A Worker is a special kind of object which represents an underlying
Worker thread usable in the ThreadPool.
- title - Variable in class ec.display.chart.ChartableStatistics
-
- top(int) - Method in class ec.gp.ADFStack
-
Returns the nth item in the stack (0-indexed), or null if
this goes to the bottom of the stack.
- top() - Method in class ec.util.Parameter
-
Returns the path item at the far end of the parameter.
- top_n_percent - Variable in class ec.select.GreedyOverselection
-
- topOfFloatStack(Interpreter) - Method in class ec.gp.push.PushProblem
-
Returns the top of the interpreter's float stack.
- topOfIntStack(Interpreter) - Method in class ec.gp.push.PushProblem
-
Returns the top of the interpreter's int stack.
- toroidal - Variable in class ec.spatial.Spatial1DSubpopulation
-
- tossSecondParent - Variable in class ec.gp.breed.SizeFairCrossoverPipeline
-
Should the pipeline discard the second parent after crossing over?
- tossSecondParent - Variable in class ec.gp.koza.CrossoverPipeline
-
Should the pipeline discard the second parent after crossing over?
- tossSecondParent - Variable in class ec.rule.breed.RuleCrossoverPipeline
-
Should the pipeline discard the second parent after crossing over?
- tossSecondParent - Variable in class ec.vector.breed.ListCrossoverPipeline
-
- tossSecondParent - Variable in class ec.vector.breed.VectorCrossoverPipeline
-
Should the pipeline discard the second parent after crossing over?
- toString() - Method in class ec.display.ParameterValue
-
- toString() - Method in class ec.gp.ADF
-
- toString() - Method in class ec.gp.ADFArgument
-
- toString() - Method in class ec.gp.ERC
-
This defaults to simply name() + "[" + encode() + "]".
- toString() - Method in class ec.gp.ge.GrammarFunctionNode
-
A better toString() function -- khaled
- toString() - Method in class ec.gp.ge.GrammarNode
-
- toString() - Method in class ec.gp.ge.GrammarParser
-
- toString() - Method in class ec.gp.ge.GrammarRuleNode
-
A better toString() function -- khaled
- toString() - Method in class ec.gp.GPFunctionSet
-
Returns the name.
- toString() - Method in class ec.gp.GPNode
-
Returns a Lisp-like atom for the node which can be read in again by computer.
- toString() - Method in class ec.gp.GPNodeConstraints
-
- toString() - Method in class ec.gp.GPTreeConstraints
-
- toString() - Method in class ec.gp.GPType
-
Returns the type's name
- toString() - Method in class ec.gp.push.Nonterminal
-
- toString() - Method in class ec.Individual
-
Overridden here because hashCode() is not expected to return the pointer
to the object.
- toString() - Method in class ec.rule.RuleConstraints
-
Converting the rule to a string ( the name )
- toString() - Method in class ec.rule.RuleSetConstraints
-
Converting the rule to a string ( the name )
- toString() - Method in class ec.util.DataPipe
-
- toString() - Method in class ec.util.Parameter
-
- toString() - Method in class ec.util.ParameterDatabase
-
- toString() - Method in class ec.util.ReflectedObject
-
- toStringForError() - Method in class ec.gp.GPNode
-
Returns a description of the node that can make it easy to identify
in error messages (by default, at least its name and the tree it's found in).
- toStringForHumans() - Method in class ec.gp.ERC
-
You might want to override this to return a special human-readable version of the erc value; otherwise this defaults to toString(); This should be something that resembles a LISP atom.
- toStringForHumans() - Method in class ec.gp.GPNode
-
Returns a Lisp-like atom for the node which is intended for human
consumption, and not to be read in again.
- toStringForHumans() - Method in class ec.gp.push.Nonterminal
-
- toStringForHumans() - Method in class ec.gp.push.Terminal
-
- totalFitnessThisGen - Variable in class ec.simple.SimpleShortStatistics
-
- totalIndsSoFar - Variable in class ec.simple.SimpleShortStatistics
-
- totalIndsThisGen - Variable in class ec.simple.SimpleShortStatistics
-
- totalSizeSoFar - Variable in class ec.simple.SimpleShortStatistics
-
- totalSizeThisGen - Variable in class ec.simple.SimpleShortStatistics
-
- TournamentSelection - Class in ec.select
-
Does a simple tournament selection, limited to the subpopulation it's
working in at the time.
- TournamentSelection() - Constructor for class ec.select.TournamentSelection
-
- transferAdditionalData(EvolutionState) - Method in class ec.eval.MasterProblem
-
This method is called by a Slave to transfer data previously loaded via receiveAdditionalData() to
a running EvolutionState at the beginning of evolution.
- traverseTreeForDepth(GPNode, ArrayList, HashMap) - Method in class ec.gp.breed.SizeFairCrossoverPipeline
-
Recursively travel the tree so that depth and subtree below are computed
only once and can be reused later.
- tree1 - Variable in class ec.gp.breed.InternalCrossoverPipeline
-
Is the first tree fixed? If not, this is -1
- tree1 - Variable in class ec.gp.breed.SizeFairCrossoverPipeline
-
Is the first tree fixed? If not, this is -1
- tree1 - Variable in class ec.gp.koza.CrossoverPipeline
-
Is the first tree fixed? If not, this is -1
- tree2 - Variable in class ec.gp.breed.InternalCrossoverPipeline
-
Is the second tree fixed? If not, this is -1
- tree2 - Variable in class ec.gp.breed.SizeFairCrossoverPipeline
-
Is the second tree fixed? If not, this is -1
- tree2 - Variable in class ec.gp.koza.CrossoverPipeline
-
Is the second tree fixed? If not, this is -1
- TREE_UNFIXED - Static variable in class ec.gp.GPBreedingPipeline
-
Standard value for an unfixed tree
- treeConstraintRepository - Variable in class ec.gp.GPInitializer
-
- treeConstraints - Variable in class ec.gp.GPInitializer
-
- treeEquals(GPTree) - Method in class ec.gp.GPTree
-
Returns true if I am "genetically" the same as tree,
though we may have different owners.
- treeHashCode() - Method in class ec.gp.GPTree
-
Returns a hash code for comparing different GPTrees.
- treeNumber() - Method in class ec.gp.GPTree
-
An expensive function which determines my tree number -- only
use for errors, etc.
- trees - Variable in class ec.gp.GPIndividual
-
- treetype - Variable in class ec.gp.GPTreeConstraints
-
The type of the root of the tree
- trials - Variable in class ec.Fitness
-
Auxiliary variable, used by coevolutionary processes, to compute the
number of trials used to compute this Fitness value.
- truesizes - Variable in class ec.gp.build.Uniform
-
- TRUNCATE - Static variable in class ec.Subpopulation
-
- tweak(EvolutionState, double[], double, double, double, double, int) - Method in class ec.pso.Particle
-
- type - Variable in class ec.gp.GPType
-
The preassigned integer value for the type
- type - Variable in class ec.util.DecodeReturn
-
The DecodeReturn type
- TYPE_RANDOM_WALK - Static variable in class ec.spatial.SpatialTournamentSelection
-
- TYPE_UNIFORM - Static variable in class ec.spatial.SpatialTournamentSelection
-
- typeFor(String, EvolutionState) - Static method in class ec.gp.GPType
-
Returns a type for a given name.
- typeRepository - Variable in class ec.gp.GPInitializer
-
TODO Comment these members.
- types - Variable in class ec.gp.GPInitializer
-
- types_h - Variable in class ec.gp.GPSetType
-
The hashtable of types in the set
- types_packed - Variable in class ec.gp.GPSetType
-
A packed, sorted array of atomic types in the set
- types_sparse - Variable in class ec.gp.GPSetType
-
A sparse array of atomic types in the set
- typicalIndsProduced() - Method in class ec.breed.BufferedBreedingPipeline
-
- typicalIndsProduced() - Method in class ec.breed.ForceBreedingPipeline
-
Returns the max of typicalIndsProduced() of all its children
- typicalIndsProduced() - Method in class ec.breed.GenerationSwitchPipeline
-
Returns the max of typicalIndsProduced() of all its children
- typicalIndsProduced() - Method in class ec.breed.MultiBreedingPipeline
-
Returns the max of typicalIndsProduced() of all its children
- typicalIndsProduced() - Method in class ec.BreedingPipeline
-
Returns the "typical" number of individuals produced -- by default
this is the minimum typical number of individuals produced by any
children sources of the pipeline.
- typicalIndsProduced() - Method in class ec.BreedingSource
-
Returns the "typical" number of individuals
generated with one call of produce(...).
- typicalIndsProduced() - Method in class ec.gp.breed.SizeFairCrossoverPipeline
-
Returns 2 * minimum number of typical individuals produced by any
sources, else 1* minimum number if tossSecondParent is true.
- typicalIndsProduced() - Method in class ec.gp.koza.CrossoverPipeline
-
Returns 2 * minimum number of typical individuals produced by any sources, else
1* minimum number if tossSecondParent is true.
- typicalIndsProduced() - Method in class ec.rule.breed.RuleCrossoverPipeline
-
Returns 2 (unless tossing the second sibling, in which case it returns 1)
- typicalIndsProduced() - Method in class ec.rule.breed.RuleMutationPipeline
-
Returns 1
- typicalIndsProduced() - Method in class ec.SelectionMethod
-
Returns 1 (the typical default value)
- typicalIndsProduced() - Method in class ec.vector.breed.ListCrossoverPipeline
-
- typicalIndsProduced() - Method in class ec.vector.breed.MultipleVectorCrossoverPipeline
-
Returns the minimum number of children that are produced per crossover
- typicalIndsProduced() - Method in class ec.vector.breed.VectorCrossoverPipeline
-
Returns 2 * minimum number of typical individuals produced by any sources, else
1* minimum number if tossSecondParent is true.