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Representation Matters: Characterisation and Impossibility Results for Interval Aggregation

hal.structure.identifierInstitute for Logic, Language and Computation [ILLC]
dc.contributor.authorEndriss, Ulle
hal.structure.identifierCentre d'économie de la Sorbonne [CES]
dc.contributor.authorNovaro, Arianna
hal.structure.identifierLaboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
dc.contributor.authorTerzopoulou, Zoi
ORCID: 0000-0001-7935-2145
dc.date.accessioned2023-01-20T15:00:42Z
dc.date.available2023-01-20T15:00:42Z
dc.date.issued2022
dc.identifier.urihttps://basepub.dauphine.psl.eu/handle/123456789/23793
dc.language.isoenen
dc.subjectAgent-based and Multi-agent Systemsen
dc.subjectComputational Social Choiceen
dc.subject.ddc006.3en
dc.titleRepresentation Matters: Characterisation and Impossibility Results for Interval Aggregationen
dc.typeCommunication / Conférence
dc.description.abstractenIn the context of aggregating intervals reflecting the views of several agents into a single interval, we investigate the impact of the form of representation chosen for the intervals involved. Specifically, we ask whether there are natural rules we can define both as rules that aggregate separately the left and right endpoints of intervals and as rules that aggregate separately the left endpoints and the interval widths. We show that on discrete scales it is essentially impossible to do so, while on continuous scales we can characterise the rules meeting these requirements as those that compute a weighted average of the endpoints of the individual intervals.en
dc.identifier.citationpages286-292en
dc.relation.ispartoftitleProceedings of the Thirty-First International Joint Conference on Artificial Intelligence (IJCAI 2022)en
dc.relation.ispartofpublnameIJCAIen
dc.relation.ispartofpublcityVienneen
dc.relation.ispartofdate2022-07
dc.relation.ispartofpages5959en
dc.relation.ispartofurlhttps://www.ijcai.org/proceedings/2022/en
dc.identifier.urlsitehttps://www.ijcai.org/proceedings/2022/41en
dc.subject.ddclabelIntelligence artificielleen
dc.relation.ispartofisbn978-1-956792-00-3en
dc.relation.conftitle31st International Joint Conference on Artificial Intelligence (IJCAI-22)en
dc.relation.confdate2022-07
dc.relation.confcityVienneen
dc.relation.confcountryAustriaen
dc.relation.forthcomingnonen
dc.identifier.doi10.24963/ijcai.2022/41en
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dc.description.halcandidatenonen
dc.description.readershiprechercheen
dc.description.audienceInternationalen
dc.relation.Isversionofjnlpeerreviewedouien
dc.date.updated2023-01-20T14:55:33Z
hal.export.arxivnonen
hal.export.pmcnonen
hal.hide.repecnonen
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