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Two Views of Classifier Systems

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Advances in Learning Classifier Systems (IWLCS 2001)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2321))

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Abstract

This work suggests two ways of looking at 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.

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Kovacs, T. (2002). Two Views of Classifier Systems. In: Lanzi, P.L., Stolzmann, W., Wilson, S.W. (eds) Advances in Learning Classifier Systems. IWLCS 2001. Lecture Notes in Computer Science(), vol 2321. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48104-4_6

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  • DOI: https://doi.org/10.1007/3-540-48104-4_6

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