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dc.contributorEscuela de Ingenierias Industrial e Informaticaes_ES
dc.contributor.authorMatellán Olivera, Vicente 
dc.contributor.authorFernández Llamas, Camino 
dc.contributor.otherArquitectura y Tecnologia de Computadoreses_ES
dc.date1998-10-26
dc.date.accessioned2012-11-09T10:58:35Z
dc.date.available2012-11-09T10:58:35Z
dc.date.issued2012-11-09
dc.identifier.citationRobotics and Autonomous Systems, 1998, vol. 25, n. 1-2es_ES
dc.identifier.urihttp://hdl.handle.net/10612/1988
dc.descriptionP. 33-41es_ES
dc.description.abstractThis paper concerns the learning of basic behaviors in an autonomous robot. It presents a method to adapt basic reactive behaviors using a genetic algorithm. Behaviors are implemented as fuzzy controllers and the genetic algorithm is used to evolve their rules. These rules will be formulated in a fuzzy way using prefixed linguistic labels. In order to test the rules obtained in each generation of the genetic evolution process, a real robot has been used. Numerical results from the evolution rate of the different experiments, as well as an example of the fuzzy rules obtained, are presented and discussedes_ES
dc.languageenges_ES
dc.publisherElsevieres_ES
dc.subjectInformáticaes_ES
dc.subject.otherRobots autónomoses_ES
dc.subject.otherFuzzyes_ES
dc.subject.otherAlgoritmos genéticoses_ES
dc.subject.otherBúsquedaes_ES
dc.titleGenetic learning of fuzzy reactive controllerses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.description.peerreviewedSIes_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES


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