An introduction to genetic algorithms
An introduction to genetic algorithms
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Evolution Strategies: An Alternative Evolutionary Algorithm
AE '95 Selected Papers from the European conference on Artificial Evolution
Solution concepts in coevolutionary algorithms
Solution concepts in coevolutionary algorithms
A game-theoretic and dynamical-systems analysis of selection methods in coevolution
IEEE Transactions on Evolutionary Computation
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We examine the dynamical and game-theoretic properties of several selection methods in the context of two-population coevolution. The methods we examine are fitness-proportional, linear rank, truncation, and (μ,λ)-ES selection. We use simple symmetric variable-sum games in an evolutionary game-theoretic framework. Our results indicate that linear rank, truncation, and (μ,λ)-ES selection are somewhat better-behaved in a two-population setting than in the one-population case analyzed by Ficici et al. [4]. These alternative selection methods maintain the Nash-equilibrium attractors found in proportional selection, but also add non-Nash attractors as well as regions of phase-space that lead to cyclic dynamics. Thus, these alternative selection methods do not properly implement the Nash-equilibrium solution concept.