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dc.contributorEscuela de Ingenierias Industrial e Informaticaes_ES
dc.contributor.authorMatellán Olivera, Vicente 
dc.contributor.authorMolina, José Manuel
dc.contributor.authorSánz, Javier
dc.contributor.authorFernández Llamas, Camino 
dc.contributor.otherArquitectura y Tecnologia de Computadoreses_ES
dc.date2012-10-11
dc.date.accessioned2012-10-11T13:01:54Z
dc.date.available2012-10-11T13:01:54Z
dc.date.issued2012-10-11
dc.identifier.citationIV European Workshop on Learning Robots, 1995, Karlsruhe (Alemania)es_ES
dc.identifier.urihttp://hdl.handle.net/10612/1907
dc.description.abstractThis paper is concerned with the learning of basic behaviors in autonomous robots. In this way, we present a method for the adaptation of basic reactive behaviors implemented as fuzzy controllers applying a genetic algorithm to the evolution of the fuzzy rule system. In this sense, we show our experiments in the evolution of control rules based on symbolic concepts represented as linguistic labels. The rules will be formulated in a fuzzy way and in order to test the rules obtained in each generation of the genetic algorithm a real robot has been used. The individual with the best performance is chosen to generate a new population: the elite strategy. All the new individuals were tested in the same real environment. In conclusion, the individuals of the last generation offer a set of rules that provides better performance than the ones designed by a non-expert designeres_ES
dc.languageenges_ES
dc.subjectInformáticaes_ES
dc.subject.otherRobóticaes_ES
dc.subject.otherRobots autónomoses_ES
dc.subject.otherFuzzyes_ES
dc.subject.otherAprendizajees_ES
dc.titleLearning Fuzzy Reactive Behaviors in Autonomous Robotses_ES
dc.typeinfo:eu-repo/semantics/conferenceObjectes_ES
dc.type.otherinfo:eu-repo/semantics/lecturees_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES


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