Evolution of tags in classifier systems

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dc.contributor.author Sanchis de Miguel, María Araceli
dc.contributor.author Molina López, José Manuel
dc.contributor.author Isasi Viñuela, Pedro
dc.contributor.author Segovia, Javier
dc.date.accessioned 2011-08-01T08:52:24Z
dc.date.available 2011-08-01T08:52:24Z
dc.date.issued 2001
dc.identifier.bibliographicCitation Journal of Intelligent Systems, 2001, vol. 11, n. 5, p. 313-342
dc.identifier.issn 0334-1860
dc.identifier.uri http://hdl.handle.net/10016/10200
dc.description.abstract One of the major problems related to Classifier Systems is the loss of rules. This loss is caused by the Genetic Algorithm being applied on the entire population of rules jointly. Obviously, the genetic operators discriminate rules by the strength value, such that evolution favors the generation of the stronger rules. When the learning process presents individual cases and allows the system to learn gradually from these cases, each learning interval with a set of individual cases can lead the strength to be distributed in favor of a given type of rules that would, in turn, be favored by the Genetic Algorithm. Basically, the idea is to divide rules into groups such that they are forced to remain in the system. This contribution is a method of learning that allows similar knowledge to be grouped. A field in which knowledge-based systems researchers have done a lot of work is concept classification and the relationships that are established between these concepts in the stage of knowledge conceptualization for later formalization. This job of classifying and searching relationships is performed in the proposed Classifier System by means of a mechanism, Tags, that allows the classification and the relationships to be discovered without the need for expert knowledge.
dc.format.mimetype application/pdf
dc.format.mimetype text/plain
dc.language.iso eng
dc.publisher Freund Publishing House Ltd
dc.subject.other Evolutionary computation
dc.subject.other Learning classifier systems
dc.subject.other Rule based systems
dc.subject.other Knowledge acquisition
dc.subject.other Knowledge classification
dc.subject.other Internal tags
dc.title Evolution of tags in classifier systems
dc.type article
dc.type.review PeerReviewed
dc.description.status Publicado
dc.subject.eciencia Informática
dc.rights.accessRights openAccess
dc.identifier.publicationfirstpage 313
dc.identifier.publicationissue 5
dc.identifier.publicationlastpage 342
dc.identifier.publicationtitle Journal of Intelligent Systems
dc.identifier.publicationvolume 11
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