Treewidth-aware Reductions of Normal ASP to SAT -- Is Normal ASP Harder than SAT after All?
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Abstract (arXiv)
Answer Set Programming (ASP) is a paradigm for modeling and solving problems for knowledge representation and reasoning. There are plenty of results dedicated to studying the hardness of (fragments of) ASP. So far, these studies resulted in characterizations in terms of computational complexity as well as in fine-grained insights presented in form of dichotomy-style results, lower bounds when translating to other formalisms like propositional satisfiability (SAT), and even detailed parameterized complexity landscapes. A generic parameter in parameterized complexity originating from graph theory is the so-called treewidth, which in a sense captures structural density of a program. Recently, there was an increase in the number of treewidth-based solvers related to SAT. While there are translations from (normal) ASP to SAT, no reduction that preserves treewidth or at least keeps track of the treewidth increase is known. In this paper we propose a novel reduction from normal ASP to SAT that is aware of the treewidth, and guarantees that a slight increase of treewidth is indeed sufficient. Further, we show a new result establishing that, when considering treewidth, already the fragment of normal ASP is slightly harder than SAT (under reasonable assumptions in computational complexity). This also confirms that our reduction probably cannot be significantly improved and that the slight increase of treewidth is unavoidable. Finally, we present an empirical study of our novel reduction from normal ASP to SAT, where we compare treewidth upper bounds that are obtained via known decomposition heuristics. Overall, our reduction works better with these heuristics than existing translations.
Key facts. Cited by 8 papers in the map (data through 14 Oct 2026). Builds on 21 of its 95 references that are in the map. First posted on arXiv 7 Oct 2022.
Builds on
21 of 95 references.
References · 21
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9 more
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Built on by
Citing papers per year: 2023: 3; 2024: 3; 2025: 2.
8 papers.
- 2023IASCAR: Incremental Answer Set Counting by Anytime Refinementcited by 2
- 2023Current and Future Challenges in Knowledge Representation and Reasoningcited by 1
- 2025Epistemic Logic Programs: Non-Ground and Counting Complexitycited by 1
- 2023Characterizing Structural Hardness of Logic Programs: What makes Cycles and Reachability Hard for Treewidth?cited by 0
- 2024Extended Version of: On the Structural Hardness of Answer Set Programming: Can Structure Efficiently Confine the Power of Disjunctions?cited by 0
- 2024Rejection in Abstract Argumentation: Harder Than Acceptance?cited by 0
- 2024Solving Decision Theory Problems with Probabilistic Answer Set Programmingcited by 0
- 2025Counting Answer Sets of Disjunctive Answer Set Programscited by 0
- 2025Counting Answer Sets of Disjunctive Answer Set Programs15 Jul 2025
- 2025Epistemic Logic Programs: Non-Ground and Counting Complexity31 Jan 2025
- 2024Solving Decision Theory Problems with Probabilistic Answer Set Programming21 Aug 2024
- 2024Rejection in Abstract Argumentation: Harder Than Acceptance?20 Aug 2024
- 2024Extended Version of: On the Structural Hardness of Answer Set Programming: Can Structure Efficiently Confine the Power of Disjunctions?5 Feb 2024
- 2023IASCAR: Incremental Answer Set Counting by Anytime Refinement13 Nov 2023
- 2023Current and Future Challenges in Knowledge Representation and Reasoning8 Aug 2023
- 2023Characterizing Structural Hardness of Logic Programs: What makes Cycles and Reachability Hard for Treewidth?18 Jan 2023