Abstract
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.
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Troc, M., Unold, O. (2008). Learning Classifier System with Self-adaptive Discovery Mechanism. In: Krasnogor, N., Nicosia, G., Pavone, M., Pelta, D. (eds) Nature Inspired Cooperative Strategies for Optimization (NICSO 2007). Studies in Computational Intelligence, vol 129. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-78987-1_25
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DOI: https://doi.org/10.1007/978-3-540-78987-1_25
Publisher Name: Springer, Berlin, Heidelberg
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Online ISBN: 978-3-540-78987-1
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