Finding Multimodal Solutions Using Restricted Tournament Selection
Proceedings of the 6th International Conference on Genetic Algorithms
Introduction to Evolutionary Computing
Introduction to Evolutionary Computing
Solution concepts in coevolutionary algorithms
Solution concepts in coevolutionary algorithms
Proceedings of the 9th annual conference on Genetic and evolutionary computation
New methods for competitive coevolution
Evolutionary Computation
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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.