Academic Progress
Masters Degree
Qualifying Exams
PhD Course work
Comprehensive Exams
Dissertation Proposal
Dissertation Hours
Dissertation Defense
Research
The goal of my research was to help bridge the gap between evolutionary
algorithm (EA) theory and practice. I developed a set of tools
 based on quantitative genetics theory  which practitioners can use to
instrument an existing EA. The data collected during a run will allow one to
identify and diagnose problems by observing how the algorithm searches the
problem landscape.
Publications

Jeffrey K. Bassett (2012)

Methods for Improving the Design and Performance of Evolutionary Algorithms.
PhD thesis, George Mason University, Fairfax, VA.
[PDF]

Jeffrey K. Bassett, Uday Kamath and Kenneth A. De Jong (2012)

A New Methodology for the GP Theory Toolbox.
In Proceedings of Genetic and Evolutionary Computation Conference  GECCO2012.
[PDF]

Jeffrey K. Bassett and Kenneth A. De Jong (2011)

Using multivariate quantitative genetics theory to assist in EA customization.
In Proceedings of the 11th workshop proceedings on Foundations of genetic algorithms.
Pages 219230, ACM.
[PDF]

Jeffrey K. Bassett, Mark Coletti, and Kenneth A. De Jong (2009)

The Relationship Between Evolvability and Bloat.
In Proceedings of Genetic and Evolutionary Computation Conference  GECCO2009.
Pages 1899–1900 (Poster), ACM Press.
[PDF]
[Poster]

Jeffrey K. Bassett, Mitchell A. Potter, and Kenneth A. De Jong (2005)

Applying Price's Equation to Survival Selection.
In Proceedings of Genetic and Evolutionary Computation Conference  GECCO2005.
Pages 1371–1378.
ACM Press.
[PDF]
 Jeffrey K. Bassett and Mitchell A. Potter and Kenneth A. De Jong (2004)
 Looking Under the EA Hood with Price's Equation.
In Genetic and Evolutionary Computation Conference – GECCO2004, SpringerVerlag.
[PDF]
 Mitchell A. Potter and Jeffrey K. Bassett and Kenneth A. De Jong (2003)
 Visualizing evolvability with Price's equation.
In Proceedings of the 2003 Congress on Evolutionary Computation, IEEE Press.
[PDF]
 Jeffrey K. Bassett (2002)
 A Study of Generalization Techniques in Evolutionary Rule Learning.
Masters thesis, George Mason University, Fairfax VA, USA.
[PDF] [PostScript] [gzipped PostScript]
 Jeffrey K. Bassett, R. Paul Wiegand and Kenneth A. De Jong (2001)
 Evolving Multi–Agent Behaviors Using a Tunable Problem Landscape.
In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO) 2001, pages 1133 (Poster), Morgan Kaufmann Publishers.
 Jeffrey K. Bassett and Kenneth A. De Jong (2000)
 Evolving Behaviors for Cooperating Agents.
In Proceedings of the Twelfth International Symposium on Methodologies for Intelligent Systems, Z. Ras and S. Ohsuga editor(s), pages 157–165, SpringerVerlag.
[PDF] [PostScript] [gzipped PostScript]
Contact Information
Jeff Bassett
George Mason University
4400 University Dr.
Krasnow Institute, MS 2A1
Fairfax, VA 22030
Located near here
office: Room 212
email: jbassett@cs.gmu.edu
phone: (703) 9934380
Udated on 8/22/2015 Jeffrey Bassett