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A timing analysis of convergence to fitness sharing equilibrium

  • Jeffrey Horn
  • David E. Goldberg
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1498)

Abstract

Fitness sharing has been shown to be an effective niching mechanism in genetic algorithms (GAs). Sharing allows GAs to maintain multiple, cooperating “species” in a single population for many generations under severe selective pressure. While recent studies have shown that the maintenance time for niching equilibrium is long, it has never been shown that the time it takes to reach equilibrium is sufficiently fast. While experiments indicate that selection under fitness sharing drives the population to equilibrium just as fast and as effectively as selection alone drives the simple GA to a uniform population, we can now show analytically that this is the case.

Keywords

Genetic Algorithm Convergence Time Learning Classifier System Proportionate Selection Initial Proportion 
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 1998

Authors and Affiliations

  • Jeffrey Horn
    • 1
  • David E. Goldberg
    • 2
  1. 1.Northern Michigan UniversityMarquetteUSA
  2. 2.Illinois Genetic Algorithms LaboratoryUniversity of Illinois at Urbana-ChampaignUSA

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