2005 | OriginalPaper | Buchkapitel
Learning Classifier System with Convergence and Generalization
verfasst von : Atsushi Wada, Keiki Takadama, Katsunori Shimohara, Osamu Katai
Erschienen in: Foundations of Learning Classifier Systems
Verlag: Springer Berlin Heidelberg
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Learning Classifier Systems (LCSs) are rule-based systems whose rules are named
classifiers
. The original LCS was introduced by Holland [1, 2], and was intended to be a framework to study learning in condition-action rules. It included the distinctive features of a
generalization
mechanism in rule conditions and a
rule discovery
mechanism using genetic algorithms (GAs) [3]. Later, this original LCS was revised to its “standard form”[4], which produced many variants [5–8].