Computing Preferred Extensions in Abstract Argumentation: a SAT-based Approach
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Abstract (arXiv)
This paper presents a novel SAT-based approach for the computation of extensions in abstract argumentation, with focus on preferred semantics, and an empirical evaluation of its performances. The approach is based on the idea of reducing the problem of computing complete extensions to a SAT problem and then using a depth-first search method to derive preferred extensions. The proposed approach has been tested using two distinct SAT solvers and compared with three state-of-the-art systems for preferred extension computation. It turns out that the proposed approach delivers significantly better performances in the large majority of the considered cases.
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). First posted on arXiv 18 Oct 2013.
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Citing papers per year: 2021: 1; 2022: 1.
2 papers.
- 2021Online Handbook of Argumentation for AI: Volume 2cited by 0
- 2022Fuzzy Labeling Semantics for Quantitative Argumentationcited by 0
- 2022Fuzzy Labeling Semantics for Quantitative Argumentation15 Jul 2022
- 2021Online Handbook of Argumentation for AI: Volume 216 Jun 2021