Skeptical Reasoning with Preferred Semantics in Abstract Argumentation without Computing Preferred Extensions

Matthias Thimm, Federico Cerutti, Mauro Vallati

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

We address the problem of deciding skeptical acceptance wrt. preferred semantics of an argument in abstract argumentation frameworks, i. e., the problem of deciding whether an argument is contained in all maximally admissible sets, a.k.a. preferred extensions. State-of-the-art algorithms solve this problem with iterative calls to an external SATsolver to determine preferred extensions. We provide a new characterisation of skeptical acceptance wrt. preferred semantics that does not involve the notion of a preferred extension. We then develop a new algorithm that also relies on iterative calls to an external SAT-solver but avoids the costly part of maximising admissible sets. We present the results of an experimental evaluation that shows that this new approach significantly outperforms the state of the art. We also apply similar ideas to develop a new algorithm for computing the ideal extension.
Original languageEnglish
Title of host publicationProceedings of the 30th International Joint Conference on Artificial Intelligence
Subtitle of host publicationIJCAI 2021
PublisherInternational Joint Conferences on Artificial Intelligence
Number of pages7
Publication statusAccepted/In press - 29 Apr 2021
Event30th International Joint Conference on Artificial Intelligence - Montreal-themed Virtual Reality due to COVID-19, Virtual (Montreal), Canada
Duration: 21 Aug 202126 Aug 2021
Conference number: 30
https://ijcai-21.org/

Conference

Conference30th International Joint Conference on Artificial Intelligence
Abbreviated titleIJCAI-21
CountryCanada
CityVirtual (Montreal)
Period21/08/2126/08/21
Internet address

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