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hal.structure.identifier
dc.contributor.authorBaumeister, Dorothea
hal.structure.identifierInstitut national Polytechnique de Grenoble [INP GRENOBLE]
dc.contributor.authorBouveret, Sylvain
HAL ID: 976
ORCID: 0000-0002-1570-5244
hal.structure.identifierLaboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
dc.contributor.authorLang, Jérôme
hal.structure.identifier
dc.contributor.authorNguyen, Nhan-Tam
hal.structure.identifier
dc.contributor.authorNguyen, Trung Thanh
hal.structure.identifier
dc.contributor.authorRothe, Jörg
dc.date.accessioned2017-03-28T14:39:50Z
dc.date.available2017-03-28T14:39:50Z
dc.date.issued2014
dc.identifier.urihttps://basepub.dauphine.fr/handle/123456789/16448
dc.language.isoenen
dc.subjectsocial choiceen
dc.subjectvotingen
dc.subject.ddc003en
dc.titleScoring Rules for the Allocation of Indivisible Goodsen
dc.typeCommunication / Conférence
dc.description.abstractenWe define a family of rules for dividing m indivisible goods among agents, parameterized by a scoring vector and a social welfare aggregation function. We assume that agents' preferences over sets of goods are additive, but that the input is ordinal: each agent simply ranks single goods. Similarly to (positional) scoring rules in voting, a scoring vector s = (s1,...,sm) consists of m nonincreasing nonnegative weights, where si is the score of a good assigned to an agent who ranks it in position i. The global score of an allocation for an agent is the sum of the scores of the goods assigned to her. The social welfare of an allocation is the aggregation of the scores of all agents, for some aggregation function * such as, typically, + or min. The rule associated with s and * maps a profile to (one of) the allocation(s) maximizing social welfare. After defining this family of rules, and focusing on some key examples, we investigate some of the social-choice-theoretic properties of this family of rules, such as various kinds of monotonicity, separability, envy-freeness, and Pareto efficiency.en
dc.identifier.citationpages75-80en
dc.relation.ispartoftitleECAI'14 Proceedings of the Twenty-first European Conference on Artificial Intelligenceen
dc.relation.ispartofeditorSchaub, Torsten
dc.relation.ispartofeditorFriedrich, Gerhard
dc.relation.ispartofeditorO'Sullivan, Barry
dc.relation.ispartofpublnameIos Pressen
dc.relation.ispartofpublcityAmsterdamen
dc.relation.ispartofdate2014-08
dc.relation.ispartofpages1232en
dc.subject.ddclabelRecherche opérationnelleen
dc.relation.ispartofisbn978-1-61499-418-3en
dc.relation.conftitle21st European Conference on Artificial Intelligence (ECAI'14)en
dc.relation.confdate2014-08
dc.relation.confcityPragueen
dc.relation.confcountryCzech Republicen
dc.relation.forthcomingnonen
dc.identifier.doi10.3233/978-1-61499-419-0-75en
dc.description.ssrncandidatenonen
dc.description.halcandidateouien
dc.description.readershiprechercheen
dc.description.audienceInternationalen
dc.relation.Isversionofjnlpeerreviewednonen
dc.relation.Isversionofjnlpeerreviewednonen
dc.date.updated2017-03-28T14:25:31Z
hal.identifierhal-01497489*
hal.version1*
hal.author.functionaut
hal.author.functionaut
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