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<OAI-PMH schemaLocation=http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd> <responseDate>2018-01-15T15:38:15Z</responseDate> <request identifier=oai:HAL:hal-00520610v1 verb=GetRecord metadataPrefix=oai_dc>http://api.archives-ouvertes.fr/oai/hal/</request> <GetRecord> <record> <header> <identifier>oai:HAL:hal-00520610v1</identifier> <datestamp>2017-12-21</datestamp> <setSpec>type:COMM</setSpec> <setSpec>subject:info</setSpec> <setSpec>collection:UNIV-AG</setSpec> <setSpec>collection:BNRMI</setSpec> </header> <metadata><dc> <publisher>HAL CCSD</publisher> <title lang=en>Speedup character-based matching in learning classifier systems with Xor</title> <creator>Enée, Gilles</creator> <creator>Peroumalnaïk, Mathias</creator> <contributor>Laboratoire de Mathématiques Informatique et Applications (LAMIA) ; Université des Antilles et de la Guyane (UAG)</contributor> <description>International audience</description> <source>Proceedings of the 12th annual conference comp on Genetic and evolutionary computation</source> <source>Genetic And Evolutionary Computation Conference</source> <coverage>Portland, Oregon, United States</coverage> <contributor>ACM</contributor> <publisher>ACM</publisher> <identifier>hal-00520610</identifier> <identifier>https://hal.archives-ouvertes.fr/hal-00520610</identifier> <source>https://hal.archives-ouvertes.fr/hal-00520610</source> <source>ACM. Genetic And Evolutionary Computation Conference, Jul 2010, Portland, Oregon, United States. ACM, pp.1879-1884, 2010, 〈10.1145/1830761.1830820〉</source> <identifier>DOI : 10.1145/1830761.1830820</identifier> <relation>info:eu-repo/semantics/altIdentifier/doi/10.1145/1830761.1830820</relation> <language>en</language> <subject lang=en>learning classifier system</subject> <subject lang=en>matching algorithm</subject> <subject>F.2.2 Nonnumerical Algorithms and Problems</subject> <subject>[INFO.INFO-CC] Computer Science [cs]/Computational Complexity [cs.CC]</subject> <type>info:eu-repo/semantics/conferenceObject</type> <type>Conference papers</type> <description lang=en>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.</description> <date>2010-07-06</date> </dc> </metadata> </record> </GetRecord> </OAI-PMH>