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Evolutionary Computation

Fall 1994, Vol. 2, No. 3, Pages 199-220
(doi: 10.1162/evco.1994.2.3.199)
© 1994 by the Massachusetts Institute of Technology
Memory Exploitation in Learning Classifier Systems
Article PDF (1.3 MB)
Abstract

Learning classifier systems (LCSs) offer a unique opportunity to study the adaptive exploitation of memory. Because memory is manipulated in the form of simple internal messages in the LCS, one can easily and carefully examine the development of a system of internal memory symbols. This study examines the LCS applied to a problem whose only performance goal is the effective exploitation of memory. Experimental results show that the genetic algorithm forms a relatively effective set of internal memory symbols, but that this effectiveness is directly limited by the emergence of parasite rules. The results indicate that the emergence of parasites may be an inevitable consequence in a system that must evolve its own set of internal memory symbols. The paper's primary conclusion is that the emergence of parasites is a fundamental obstacle in such problems. To overcome this obstacle, it is suggested that the LCS must form larger, multirule structures. In such structures, parasites can be more accurately evaluated and thus eliminated. This effect is demonstrated through a preliminary evaluation of a classifier corporation scheme. Final comments present future directions for research on memory exploitation in the LCS and similar evolutionary computing systems.