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Predicting opponent actions in the RoboSoccer

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dc.affiliation.dptoUC3M. Departamento de Informáticaes
dc.affiliation.grupoinvUC3M. Grupo de Investigación: Computación Evolutiva y Redes Neuronales (EVANNAI)es
dc.contributor.authorLedezma Espino, Agapito Ismael
dc.contributor.authorAler, Ricardo
dc.contributor.authorSanchis de Miguel, María Araceli
dc.contributor.authorBorrajo Millán, Daniel
dc.date.accessioned2009-12-18T08:36:58Z
dc.date.available2009-12-18T08:36:58Z
dc.date.issued2002-10
dc.descriptionProceeding of: IEEE International Conference on Systems, Man, and Cybernetics (SMC-2002), 6-9 Oct. 2002, Hammamet, Tunez
dc.description.abstractA very important issue in multi-agent systems is that of adaptability to other agents, be it to cooperate or to compete. In competitive domains, the knowledge about the opponent can give any player a clear advantage. In previous work, we acquired models of another agent (the opponent) based only on the observation of its inputs and outputs (its behavior) by formulating the problem as a classification task. In this paper we extend this previous work to the RoboCup domain. However, we have found that models based on a single classifier have bad accuracy, To solve this problem, In this paper we propose to decompose the learning task into two tasks: learning the action name (i.e. kick or dash) and learning the parameter of that action. By using this hierarchical learning approach accuracy results improve, and at worst, the agent can know what action the opponent will carry out, even if there is no high accuracy on the action parameter.
dc.description.statusPublicado
dc.format.mimetypeapplication/pdf
dc.identifier.bibliographicCitationIEEE International Conference on Systems, Man and Cybernetics, 2002, vol. 7
dc.identifier.doi10.1109/ICSMC.2002.1175692
dc.identifier.isbn0-7803-7437-1
dc.identifier.issn1062-922X
dc.identifier.publicationtitleIEEE International Conference on Systems, Man and Cybernetics
dc.identifier.publicationvolume7
dc.identifier.urihttps://hdl.handle.net/10016/6159
dc.language.isoeng
dc.publisherIEEE
dc.relation.eventdate6-9 Oct. 2002
dc.relation.eventplaceHammamet (Tunez)
dc.relation.eventtitleIEEE International Conference on Systems, Man and Cybernetics (SMC-2002)
dc.relation.publisherversionhttp://dx.doi.org/10.1109/ICSMC.2002.1175692
dc.rights© IEEE
dc.rights.accessRightsopen access
dc.subject.ecienciaInformática
dc.subject.otherGames of skill
dc.subject.otherLearning (artificial intelligence)
dc.subject.otherMobile robots
dc.subject.otherMulti-agent systems
dc.subject.otherRoboSoccer
dc.subject.otherMachine learning
dc.titlePredicting opponent actions in the RoboSoccer
dc.typeconference paper*
dc.type.reviewPeerReviewed
dspace.entity.typePublication
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