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dc.contributor.authorRIVERET, Régis
dc.contributor.authorBARONI, Pietro
dc.contributor.authorGAO, Yang
dc.contributor.authorGOVERNATORI, Guido
dc.contributor.authorROTOLO, Antonino
dc.contributor.authorSARTOR, Giovanni
dc.date.accessioned2018-12-06T13:55:44Z
dc.date.available2018-12-06T13:55:44Z
dc.date.issued2018
dc.identifier.citationAnnals of mathematics and artificial intelligence, 2018, Vol. 83, No. 1, pp. 21-71
dc.identifier.issn1012-2443
dc.identifier.issn1573-7470en
dc.identifier.urihttps://hdl.handle.net/1814/59986
dc.descriptionFirst online: 20 March 2018en
dc.description.abstractThe combination of argumentation and probability paves the way to new accounts of qualitative and quantitative uncertainty, thereby offering new theoretical and applicative opportunities. Due to a variety of interests, probabilistic argumentation is approached in the literature with different frameworks, pertaining to structured and abstract argumentation, and with respect to diverse types of uncertainty, in particular the uncertainty on the credibility of the premises, the uncertainty about which arguments to consider, and the uncertainty on the acceptance status of arguments or statements. Towards a general framework for probabilistic argumentation, we investigate a labelling-oriented framework encompassing a basic setting for rule-based argumentation and its (semi-) abstract account, along with diverse types of uncertainty. Our framework provides a systematic treatment of various kinds of uncertainty and of their relationships and allows us to back or question assertions from the literature.
dc.description.sponsorshipNational Natural Science Foundation of China (NSFC) [61602453]
dc.description.sponsorshipMarie Curie Intra-European Fellowship [PIEF-GA-2012-331472]
dc.description.sponsorshipEuropean Union's Horizon 2020 research and innovation programme under the Marie Skodowska-Curie grant [690974]
dc.language.isoen
dc.publisherSpringer (part of Springer Nature)en
dc.relation.ispartofAnnals of mathematics and artificial intelligence
dc.subjectProbabilistic argumentation
dc.subjectProbabilistic rule-based argumentation
dc.subjectProbabilistic abstract argumentation
dc.subjectProbabilistic labellings
dc.subjectAbstract argumentationen
dc.subjectBayesian networksen
dc.subjectDefeasible logicen
dc.subjectSemanticsen
dc.subjectTutorialen
dc.subjectaspic(+)en
dc.subjectSystemsen
dc.subjectSupporten
dc.subjectPrismen
dc.titleA labelling framework for probabilistic argumentation
dc.typeArticleen
dc.identifier.doi10.1007/s10472-018-9574-1
dc.identifier.volume83
dc.identifier.startpage21
dc.identifier.endpage71
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