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dc.contributor.authorTunalı, Okan
dc.contributor.authorAydoğan, R.
dc.contributor.authorSanchez-Anguix, V.
dc.date.accessioned2018-05-07T13:18:37Z
dc.date.available2018-05-07T13:18:37Z
dc.date.issued2017
dc.identifier.isbn978-3-319-69130-5
dc.identifier.urihttp://hdl.handle.net/10679/5815
dc.identifier.urihttps://link.springer.com/chapter/10.1007/978-3-319-69131-2_16
dc.descriptionDue to copyright restrictions, the access to the full text of this article is only available via subscription.
dc.description.abstractFrequency opponent modeling is one of the most widely used opponent modeling techniques in automated negotiation, due to its simplicity and its good performance. In fact, it outperforms even more complex mechanisms like Bayesian models. Nevertheless, the classical frequency model does not come without its own assumptions, some of which may not always hold in many realistic settings. This paper advances the state of the art in opponent modeling in automated negotiation by introducing a novel frequency opponent modeling mechanism, which soothes some of the assumptions introduced by classical frequency approaches. The experiments show that our proposed approach outperforms the classic frequency model in terms of evaluation of the outcome space, estimation of the Pareto frontier, and accuracy of both issue value evaluation estimation and issue weight estimation.en_US
dc.language.isoengen_US
dc.publisherSpringer International Publishingen_US
dc.relation.ispartofInternational Conference on Principles and Practice of Multi-Agent Systems PRIMA 2017: PRIMA 2017: Principles and Practice of Multi-Agent Systems
dc.rightsrestrictedAccess
dc.titleRethinking frequency opponent modeling in automated negotiationen_US
dc.typeConference paperen_US
dc.peerreviewedyes
dc.publicationstatusPublisheden_US
dc.contributor.departmentÖzyeğin University
dc.identifier.volume10621en_US
dc.identifier.startpage263en_US
dc.identifier.endpage279en_US
dc.identifier.doi10.1007/978-3-319-69131-2_16en_US
dc.subject.keywordsAgreement technologiesen_US
dc.subject.keywordsAutomated negotiationen_US
dc.subject.keywordsOpponent modelingen_US
dc.subject.keywordsMulti-agent systemsen_US
dc.identifier.scopusSCOPUS:2-s2.0-85034268075
dc.contributor.ozugradstudentTunalı, Okan


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