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hal.structure.identifierLaboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
dc.contributor.authorLang, Jérôme
dc.date.accessioned2021-10-22T14:22:28Z
dc.date.available2021-10-22T14:22:28Z
dc.date.issued2020
dc.identifier.urihttps://basepub.dauphine.psl.eu/handle/123456789/22095
dc.language.isoenen
dc.subjectdecision makingen
dc.subject.ddc006.3en
dc.titleCollective Decision Making under Incomplete Knowledge: Possible and Necessary Solutionsen
dc.typeCommunication / Conférence
dc.description.abstractenMost solution concepts in collective decision making are defined assuming complete knowledge of individuals' preferences and of the mechanism used for aggregating them. This is often unpractical or unrealistic. Under incomplete knowledge, a solution advocated by many consists in quantifying over all completions of the incomplete preference profile (or all instantiations of the incompletely specified mechanism). Voting rules can be 'modalized' this way (leading to the notions of possible and necessary winners), and also efficiency and fairness notions in fair division, stability concepts in coalition formation, and more. I give here a survey of works along this line.en
dc.subject.ddclabelIntelligence artificielleen
dc.relation.conftitleTwenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligenceen
dc.relation.confdate2020-07
dc.relation.confcityYokohamaen
dc.relation.confcountryJapanen
dc.relation.forthcomingnonen
dc.identifier.doi10.24963/ijcai.2020/680en
dc.description.ssrncandidatenon
dc.description.halcandidatenonen
dc.description.readershiprechercheen
dc.description.audienceInternationalen
dc.relation.Isversionofjnlpeerreviewednonen
dc.date.updated2021-10-22T14:21:04Z
hal.author.functionaut


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