Speedup character-based matching in learning classifier systems with Xor

Gilles Enée (1) , Mathias Peroumalnaïk (1)

1 LAMIA - Laboratoire de Mathématiques Informatique et Applications

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.

Mots clés: learning classifier system; matching algorithm

Domaines: Complexité [cs.CC]

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