Show simple item record

Pareto optimality and strategy-proofness in group argument evaluation

dc.contributor.authorAwad, Edmond
dc.contributor.authorCaminada, Martin
dc.contributor.authorPigozzi, Gabriella
dc.contributor.authorPodlaszewski, Mikolaj
dc.contributor.authorRahwan, Iyad
dc.date.accessioned2017-04-13T08:47:11Z
dc.date.available2017-04-13T08:47:11Z
dc.date.issued2017
dc.identifier.issn0955-792X
dc.identifier.urihttps://basepub.dauphine.fr/handle/123456789/16508
dc.language.isoenen
dc.subjectArgumentation
dc.subjectStrategy-proofness
dc.subjectPareto optimality
dc.subjectJudgment aggregation
dc.subject.ddc006.3en
dc.titlePareto optimality and strategy-proofness in group argument evaluation
dc.typeArticle accepté pour publication ou publié
dc.description.abstractenAn inconsistent knowledge base can be abstracted as a set of arguments and a defeat relation among them. There can be more than one consistent way to evaluate such an argumentation graph. Collective argument evaluation is the problem of aggregating the opinions of multiple agents on how a given set of arguments should be evaluated. It is crucial not only to ensure that the outcome is logically consistent, but also satisfies measures of social optimality and immunity to strategic manipulation. This is because agents have their individual preferences about what the outcome ought to be. In the current paper, we analyze three previously introduced argument-based aggregation operators with respect to Pareto optimality and strategy proofness under different general classes of agent preferences. We highlight fundamental trade-offs between strategic manipulability and social optimality on one hand, and classical logical criteria on the other. Our results motivate further investigation into the relationship between social choice and argumentation theory. The results are also relevant for choosing an appropriate aggregation operator given the criteria that are considered more important, as well as the nature of agents' preferences
dc.relation.isversionofjnlnameJournal of logic and computation
dc.relation.isversionofjnlvol27
dc.relation.isversionofjnlissue8
dc.relation.isversionofjnldate2017
dc.relation.isversionofjnlpages2581–2609
dc.relation.isversionofdoi10.1093/logcom/exx017
dc.relation.isversionofjnlpublisherOxford University Press
dc.subject.ddclabelIntelligence artificielleen
dc.relation.forthcomingnonen
dc.relation.forthcomingprintnonen
dc.description.ssrncandidatenon
dc.description.halcandidatenon
dc.description.readershiprecherche
dc.description.audienceInternational
dc.relation.Isversionofjnlpeerreviewedoui
dc.date.updated2018-01-08T10:25:40Z
hal.identifierhal-01649414*
hal.version1*
hal.update.actionupdateMetadata*


Files in this item

Thumbnail
Name:
Pareto_optimaly.pdf
Size:
756.5Kb
Format:
PDF
View/Open

This item appears in the following Collection(s)

Show simple item record