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hal.structure.identifier
dc.contributor.authorGrossi, Davide*
hal.structure.identifierLaboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
dc.contributor.authorPigozzi, Gabriella*
dc.date.accessioned2015-04-14T17:14:28Z
dc.date.available2015-04-14T17:14:28Z
dc.date.issued2014
dc.identifier.urihttps://basepub.dauphine.fr/handle/123456789/14931
dc.language.isoenen
dc.subjectcollective decision-makingen
dc.subject.ddc006.3en
dc.titleJudgment Aggregation: A Primeren
dc.typeOuvrage
dc.description.abstractenJudgment aggregation is a mathematical theory of collective decision-making. It concerns the methods whereby individual opinions about logically interconnected issues of interest can, or cannot, be aggregated into one collective stance. Aggregation problems have traditionally been of interest for disciplines like economics and the political sciences, as well as philosophy, where judgment aggregation itself originates from, but have recently captured the attention of disciplines like computer science, artificial intelligence and multi-agent systems. Judgment aggregation has emerged in the last decade as a unifying paradigm for the formalization and understanding of aggregation problems. Still, no comprehensive presentation of the theory is available to date. This Synthesis Lecture aims at filling this gap presenting the key motivations, results, abstractions and techniques underpinning it.en
dc.publisher.nameMorgan & Claypool Publishersen
dc.identifier.citationpages151en
dc.relation.ispartofseriestitleSynthesis Lectures on Artificial Intelligence and Machine Learningen
dc.relation.isversionofbkurlhttp://dx.doi.org/10.2200/S00559ED1V01Y201312AIM027en
dc.subject.ddclabelIntelligence artificielleen
dc.identifier.citationdate2014-03
dc.relation.forthcomingnonen
dc.description.halcandidateoui
dc.description.readershiprecherche
dc.description.audienceInternational
hal.identifierhal-01497079*
hal.version1*
hal.update.actionupdateMetadata*
hal.author.functionaut
hal.author.functionaut


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