Learning Classifier System with Convergence and Generalization

Abstract

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].