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dc.contributor.authorEndriss, Ulle
dc.contributor.authorMaudet, Nicolas
dc.contributor.authorFariba, Sadri
dc.contributor.authorFrancesca, Toni
dc.date.accessioned2010-01-12T09:14:43Z
dc.date.available2010-01-12T09:14:43Z
dc.date.issued2006
dc.identifier.urihttps://basepub.dauphine.fr/handle/123456789/2875
dc.language.isoenen
dc.subjectSystème multi-agentsen
dc.subject.ddc006.3en
dc.titleNegotiating Socially Optimal Allocations of Resourcesen
dc.typeArticle accepté pour publication ou publié
dc.contributor.editoruniversityotherDepartment of Computing, Imperial College London;Royaume-Uni
dc.contributor.editoruniversityotherUniversity of Amsterdam;Pays-Bas
dc.description.abstractenA multiagent system may be thought of as an artificial society of autonomous software agents and we can apply concepts borrowed from welfare economics and social choice theory to assess the social welfare of such an agent society. In this paper, we study an abstract negotiation framework where agents can agree on multilateral deals to exchange bundles of indivisible resources. We then analyse how these deals affect social welfare for different instances of the basic framework and different interpretations of the concept of social welfare itself. In particular, we show how certain classes of deals are both sufficient and necessary to guarantee that a socially optimal allocation of resources will be reached eventually.en
dc.relation.isversionofjnlnameThe Journal of Artificial Intelligence Research
dc.relation.isversionofjnlvol25en
dc.relation.isversionofjnlissue3en
dc.relation.isversionofjnldate2006
dc.relation.isversionofjnlpages315–348en
dc.relation.isversionofdoihttp://dx.doi.org/doi:10.1613/jair.1870en
dc.description.sponsorshipprivateouien
dc.relation.isversionofjnlpublisherAI Access Foundationen
dc.subject.ddclabelIntelligence artificielleen


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