2008 | OriginalPaper | Buchkapitel
Learning Classifier System with Self-adaptive Discovery Mechanism
verfasst von : Maciej Troc, Olgierd Unold
Erschienen in: Nature Inspired Cooperative Strategies for Optimization (NICSO 2007)
Verlag: Springer Berlin Heidelberg
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Learning Classifier System which replaces the genetic algorithm with the evolving cooperative population of discoverers is a focus of current research. This paper presents a modified version of XCS classifier system with self-adaptive discovery module. The new model was confirmed experimentally in a multiplexer environment. The results prove that XCS with the self-adaptive method for determining mutation rate had a better performance than the classic architecture with fixed mutation.