Rationalisation of Profiles of Abstract Argumentation Frameworks: Characterisation and Complexity

Stéphane Airiau, Elise Bonzon, Ulle Endriss, Nicolas Maudet, Julien Rossit

Research output: Contribution to journalArticle

Abstract

Different agents may have different points of view. Following a popular approach in the artificial intelligence literature, this can be modeled by means of different abstract argumentation frameworks, each consisting of a set of arguments the agent is contemplating and a binary attack-relation between them. A question arising in this context is whether the diversity of views observed in such a profile of argumentation frameworks is consistent with the assumption that every individual argumentation framework is induced by a combination of, first, some basic factual attack-relation between the arguments and, second, the personal preferences of the agent concerned regarding the moral or social values the arguments under scrutiny relate to. We treat this question of rationalisability of a profile as an algorithmic problem and identify tractable and intractable cases. In doing so, we distinguish different constraints on admissible rationalisations, e.g., concerning the types of preferences used or the number of distinct values involved. We also distinguish two different semantics for rationalisability, which differ in the assumptions made on how agents treat attacks between arguments they do not report. This research agenda, bringing together ideas from abstract argumentation and social choice, is useful for understanding what types of profiles can reasonably be expected to occur in a multiagent system.
Original languageEnglish
Pages (from-to)149-177
Number of pages29
JournalJournal of Artificial Intelligence Research
Volume60
StatePublished - 2017
Externally publishedYes

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