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SAT-Based Approaches to Reasoning in Choice Logics
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A4 Artikkeli konferenssijulkaisussa
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en
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8
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ECAI 2024 - 27th European Conference on Artificial Intelligence, Including 13th Conference on Prestigious Applications of Intelligent Systems, PAIS 2024, Proceedings, pp. 4271-4278, Frontiers in Artificial Intelligence and Applications
Abstract
Representing and reasoning about preferences is a fundamental task in artificial intelligence. Various logic-based languages for representing preferences have been proposed. However, developing practical algorithms for reasoning in such logic-based languages remains a challenge due to high computational complexity. In this work, we develop practical algorithms based on Boolean satisfiability (SAT) for computing preferred models and for deciding preferred model entailment in qualitative and conjunctive choice logics QCL and CCL under the so-called minmax, lexicographic, and inclusion-based preference semantics. For each of the problem variants, we detail an algorithm which adheres to the computational complexity of the reasoning task, based on either maximum satisfiability (MaxSAT) or SAT with preferences (PrefSAT) solvers. We empirically evaluate our implementation of the algorithms, and show that our approach scales significantly better than a recently proposed answer set programming approach to computing preferred models.
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Lehtonen, T, Niskanen, A & Järvisalo, M 2024, SAT-Based Approaches to Reasoning in Choice Logics. in U Endriss, F S Melo, K Bach, A Bugarín-Diz, J M Alonso-Moral, S Barro & F Heintz (eds), ECAI 2024 - 27th European Conference on Artificial Intelligence, Including 13th Conference on Prestigious Applications of Intelligent Systems, PAIS 2024, Proceedings. Frontiers in Artificial Intelligence and Applications, IOS Press, pp. 4271-4278, European Conference on Artificial Intelligence, Santiago de Compostela, Spain, 19/10/2024. https://doi.org/10.3233/FAIA241001