|Computer Science Department : George Mason University|
EC lab Activities
GECCO Coevolution WorkshopGeorge Mason's Evolutionary Computation Laboratory organized the 2002 Coevolutionary Workshop at the 2002 Genetic of Evolutionary Computation Conference. GECCO-02 was held Tuesday July 9 through Saturday July 13 in New York city, New York (USA).
[ See below for a summary of the results of the workshop! ]
Coevolutionary algorithms promise several advantages over traditional evolutionary algorithms in terms of their adaptability and potential open-endedness. However, they also challenge us with new and difficult issues. For example, their very adaptability means that fitness assessments in the algorithm are in some sense subjective, and thus the existence of Red Queen dynamics can make it difficult to know whether real progress is being made in any objective sense and pathologies like mediocre stable states can cast doubt on whether optimization is being done at all. More generally, dynamics in these systems can be complicated and surprising. Theory and analysis of coevolutionary algorithms is far less advanced than that of traditional evolutionary algorithms, but the time has come to focus our collective attention on analysis issues more formally. The goal of this workshop is to foster and encourage open discussion about the issues surrounding the direction that analysis of coevolutionary algorithms might take in the future, as well as introducing existing theory and empirically analytical work to those who are looking for a place to start understanding coevolution.
The publications in this year's workshop focused primarily on attempting to understand how to characterize and analyze coevolution. The first paper introduces an interesting new framework for analyzing coevolutionary problems from an order-theoretic perspective. The second paper overlaps this paper slightly, using similar notions of order and ranking in order to help better understand when coevolutionary algorithms behave dynamically like a traditional evolutionary algorithm. The third paper is also quite complementary, using dominance tournament methods to allow for on-line measurement of progress during evolutionary runs. The final paper offers an empirical perspective by applying coevolution to the problem of feature construction in machine learning.
The workshop was held as a half day event, focusing on theoretical and empirical analysis of coevolutionary algorithms. The first 45 minutes was set aside for an introductory discussion, the next two hours was reserved for paper discussions, and the remaining time was dedicated to a very fruitful panel discussion.
Workshop Results Summary
We also identified a potential topic for next year's workshop:
Characteristics of Open-Endedness.
|Last updated: Wednesday September 10, 2008||webmaster|