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Finite Population Models of Co-evolution and Their Application to Haploidy versus Diploidy

  • Anthony M. L. Liekens
  • Huub M. M. ten Eikelder
  • Peter A. J. Hilbers
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2723)

Abstract

In order to study genetic algorithms in co-evolutionary environments, we construct a Markov model of co-evolution of populations with fixed, finite population sizes. In this combined Markov model, the behavior toward the limit can be utilized to study the relative performance of the algorithms. As an application of the model, we perform an analysis of the relative performance of haploid versus diploid genetic algorithms in the co-evolutionary setup, under several parameter settings. Because of the use of Markov chains, this paper provides exact stochastic results on the expected performance of haploid and diploid algorithms in the proposed co-evolutionary model.

Keywords

Genetic Algorithm Markov Chain Limit Behavior Heterozygous Individual Evolutionary Game Theory 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Anthony M. L. Liekens
    • 1
  • Huub M. M. ten Eikelder
    • 1
  • Peter A. J. Hilbers
    • 1
  1. 1.Department of Biomedical EngineeringTechnische Universiteit EindhovenEindhovenThe Netherlands

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