Speedup character-based matching in learning classifier systems with Xor

Abstract : In 2008 a scientific paper written by Butz and al. investigated Matching in Learning Classifier Systems. Matching represents at least 65% of the computational time when executing a classifier system as reported in Llora and al. We propose to modify that encoding using a fast and accurate matching replacing standard matching algorithm for character-based classifier systems.
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Communication dans un congrès
ACM. Genetic And Evolutionary Computation Conference, Jul 2010, Portland, Oregon, United States. ACM, pp.1879-1884, 2010, <10.1145/1830761.1830820>
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https://hal.archives-ouvertes.fr/hal-00520610
Contributeur : Mathias Peroumalnaïk <>
Soumis le : jeudi 23 septembre 2010 - 18:36:58
Dernière modification le : jeudi 23 septembre 2010 - 19:02:10

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Gilles Enée, Mathias Peroumalnaïk. Speedup character-based matching in learning classifier systems with Xor. ACM. Genetic And Evolutionary Computation Conference, Jul 2010, Portland, Oregon, United States. ACM, pp.1879-1884, 2010, <10.1145/1830761.1830820>. <hal-00520610>

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