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Two Views of Classifier Systems

Tim Kovacs, Two Views of Classifier Systems. Chapter in Advances in Learning Classifier Systems. P. L. Lanzi, W. Stolzmann, S. W. Wilson, (eds.). ISBN 3-540-43793-2, pp. 74–87. April 2002. PDF, 203 Kbytes.

Abstract

This work suggests two ways of looking at Michigan classifier systems; as Genetic Algorithm-based systems, and as Reinforcement Learning-based systems, and argues that the former is more suitable for traditional strength-based systems while the latter is more suitable for accuracy-based XCS. The dissociation of the Genetic Algorithm from policy determination in XCS is noted, and the two types of Michigan classifier system are contrasted with Pittsburgh systems.

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