Rushing and Strolling among Answer Sets -- Navigation Made Easy
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Abstract (arXiv)
Answer set programming (ASP) is a popular declarative programming paradigm with a wide range of applications in artificial intelligence. Oftentimes, when modeling an AI problem with ASP, and in particular when we are interested beyond simple search for optimal solutions, an actual solution, differences between solutions, or number of solutions of the ASP program matter. For example, when a user aims to identify a specific answer set according to her needs, or requires the total number of diverging solutions to comprehend probabilistic applications such as reasoning in medical domains. Then, there are only certain problem specific and handcrafted encoding techniques available to navigate the solution space of ASP programs, which is oftentimes not enough. In this paper, we propose a formal and general framework for interactive navigation towards desired subsets of answer sets analogous to faceted browsing. Our approach enables the user to explore the solution space by consciously zooming in or out of sub-spaces of solutions at a certain configurable pace. We illustrate that weighted faceted navigation is computationally hard. Finally, we provide an implementation of our approach that demonstrates the feasibility of our framework for incomprehensible solution spaces.
Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). Builds on 11 of its 70 references that are in the map. First posted on arXiv 14 Dec 2021.
Builds on
11 of 70 references.
References · 11
- 2019ASP-Core-2 Input Language Formatcited by 77
- 2014Clingo = ASP + Control: Preliminary Reportcited by 56
- 2020The Model Counting Competition 2020cited by 24
- 2017Answer Set Solving with Bounded Treewidth Revisitedcited by 9
- 2019Design and Results of the Second International Competition on Computational Models of Argumentationcited by 9
- 2017Computing LPMLN Using ASP and MLN Solverscited by 8
- 2018Debugging Non-Ground ASP Programs: Technique and Graphical Toolscited by 8
- 2020Exploiting Database Management Systems and Treewidth for Countingcited by 7
- 2017Stepwise Debugging of Answer-Set Programscited by 6
- 2018Benchmarking Crimes: An Emerging Threat in Systems Securitycited by 4
- 2016Anytime answer set optimization via unsatisfiable core shrinkingcited by 2
Built on by
Citing papers per year: 2022: 1; 2023: 1; 2024: 1; 2025: 5; 2026: 1.
9 papers.
- 2022A Quantitative Symbolic Approach to Individual Human Reasoningcited by 2
- 2023IASCAR: Incremental Answer Set Counting by Anytime Refinementcited by 2
- 2024Unit Testing in ASP Revisited: Language and Test-Driven Development Environmentcited by 2
- 2025Counting and Reasoning with Planscited by 2
- 2025Epistemic Logic Programs: Non-Ground and Counting Complexitycited by 1
- 2025Complexity of Faceted Explanations in Propositional Abductioncited by 1
- 2025Answer Set Counting and its Applicationscited by 0
- 2025Counting Answer Sets of Disjunctive Answer Set Programscited by 0
- 2026An XAI View on Explainable ASP: Methods, Systems, and Perspectivescited by 0
- 2026An XAI View on Explainable ASP: Methods, Systems, and Perspectives21 Jan 2026
- 2025Complexity of Faceted Explanations in Propositional Abduction20 Jul 2025
- 2025Counting Answer Sets of Disjunctive Answer Set Programs15 Jul 2025
- 2025Answer Set Counting and its Applications13 Feb 2025
- 2025Epistemic Logic Programs: Non-Ground and Counting Complexity31 Jan 2025
- 2025Counting and Reasoning with Plans31 Jan 2025
- 2024Unit Testing in ASP Revisited: Language and Test-Driven Development Environment4 Jan 2024
- 2023IASCAR: Incremental Answer Set Counting by Anytime Refinement13 Nov 2023
- 2022A Quantitative Symbolic Approach to Individual Human Reasoning10 May 2022