Evaluation and Diversity in Co-evolution

  • Rients P. T. van Wijngaarden
  • Edwin D. de Jong
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5199)

Abstract

This paper studies the performance of four alternative evaluation methods; two instances of the Exponential Moving average, the Elo-rating and the Glicko-rating method. These methods are tested in a co-evolutionary setup using the LINT-game, which is known to be problematic under co-evolutionary conditions. Besides the different evaluation approaches, two methods aimed at preserving diversity are tested. By using the Objective Fitness Correlation as an analytical tool for monitoring accuracy of evaluation, it is shown that actual performance of an evaluation method strongly depends on whether co-evolutionary failure occurs and that a multi-modal approach to the LINT-problem is effective in maintaining stable progress over time.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Rients P. T. van Wijngaarden
    • 1
  • Edwin D. de Jong
    • 1
  1. 1.Algorithmic Data Analysis GroupUniversiteit UtrechtThe Netherlands

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