Harnessing Incremental Answer Set Solving for Reasoning in Assumption-Based Argumentation. Issue 6 (November 2021)

• Record Type: Journal Article
• Authors: LEHTONEN, TUOMO; WALLNER, JOHANNES P.; JӒRVISALO, MATTI
• Is Part Of: Theory and practice of logic programming. Volume 21:Issue 6(2021)
• Page Start: 717
• Page End: 734
• Publication Date: 2021-11
• Subjects: answer set programming -- incremental answer set solving -- assumption-based argumentation -- structured argumentation -- algorithms -- experimental evaluation; Logic programming -- Periodicals; Artificial intelligence -- Computer programs -- Periodicals; Constraint programming (Computer science) -- Periodicals; 005.115
• DOI: 10.1017/S1471068421000296
• Languages: English
• ISSNs: 1471-0684

Abstract

Abstract: Assumption-based argumentation (ABA) is a central structured argumentation formalism. As shown recently, answer set programming (ASP) enables efficiently solving NP-hard reasoning tasks of ABA in practice, in particular in the commonly studied logic programming fragment of ABA. In this work, we harness recent advances in incremental ASP solving for developing effective algorithms for reasoning tasks in the logic programming fragment of ABA that are presumably hard for the second level of the polynomial hierarchy, including skeptical reasoning under preferred semantics as well as preferential reasoning. In particular, we develop non-trivial counterexample-guided abstraction refinement procedures based on incremental ASP solving for these tasks. We also show empirically that the procedures are significantly more effective than previously proposed algorithms for the tasks.