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dc.contributor.authorFernández, Antonio
dc.contributor.authorSalmerón Cerdán, Antonio
dc.date.accessioned2017-07-05T09:18:59Z
dc.date.available2017-07-05T09:18:59Z
dc.date.issued2008
dc.identifier.urihttp://hdl.handle.net/10835/4889
dc.description.abstractIn this paper we introduce a chess program able to adapt its game strategy to its opponent, as well as to adapt the evaluation function that guides the search process according to its playing experience. The adaptive and learning abilities have been implemented through Bayesian networks. We show how the program learns through an experiment consisting on a series of games that point out that the results improve after the learning stage.es_ES
dc.language.isoenes_ES
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectBayesian networkses_ES
dc.subjectAdaptive learninges_ES
dc.subjectComputer chesses_ES
dc.titleBayesChess: A computer chess program based on Bayesian networkses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES
dc.identifier.doihttps://doi.org/10.1016/j.patrec.2007.06.013


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Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivatives 4.0 Internacional