Justifying Answer Sets using Argumentation
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Abstract (arXiv)
An answer set is a plain set of literals which has no further structure that would explain why certain literals are part of it and why others are not. We show how argumentation theory can help to explain why a literal is or is not contained in a given answer set by defining two justification methods, both of which make use of the correspondence between answer sets of a logic program and stable extensions of the Assumption-Based Argumentation (ABA) framework constructed from the same logic program. Attack Trees justify a literal in argumentation-theoretic terms, i.e. using arguments and attacks between them, whereas ABA-Based Answer Set Justifications express the same justification structure in logic programming terms, that is using literals and their relationships. Interestingly, an ABA-Based Answer Set Justification corresponds to an admissible fragment of the answer set in question, and an Attack Tree corresponds to an admissible fragment of the stable extension corresponding to this answer set.
Key facts. Cited by 12 papers in the map (data through 14 Oct 2026). First posted on arXiv 20 Nov 2014.
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Citing papers per year: 2021: 3; 2022: 2; 2023: 3; 2024: 2; 2025: 1; 2026: 1.
12 papers.
- 2021Argumentative XAI: A Surveycited by 67
- 2023Non-flat ABA is an Instance of Bipolar Argumentationcited by 5
- 2021exp(ASPc) : Explaining ASP Programs with Choice Atoms and Constraint Rulescited by 3
- 2024On the Correspondence of Non-flat Assumption-based Argumentation and Logic Programming with Negation as Failure in the Headcited by 2
- 2025Dialogue-based Explanations for Logical Reasoning using Structured Argumentationcited by 2
- 2021Generating explanations for answer set programming applicationscited by 1
- 2022Argumentative Explanations for Pattern-Based Text Classifierscited by 1
- 2023Explanations for Answer Set Programmingcited by 1
- 2024Automated legal reasoning with discretion to act using s(LAW)cited by 1
- 2022On Establishing Robust Consistency in Answer Set Programscited by 0
- 2023Argumentative Characterizations of (Extended) Disjunctive Logic 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
- 2025Dialogue-based Explanations for Logical Reasoning using Structured Argumentation16 Feb 2025
- 2024On the Correspondence of Non-flat Assumption-based Argumentation and Logic Programming with Negation as Failure in the Head15 May 2024
- 2024Automated legal reasoning with discretion to act using s(LAW)25 Jan 2024
- 2023Explanations for Answer Set Programming30 Aug 2023
- 2023Argumentative Characterizations of (Extended) Disjunctive Logic Programs12 Jun 2023
- 2023Non-flat ABA is an Instance of Bipolar Argumentation21 May 2023
- 2022On Establishing Robust Consistency in Answer Set Programs17 Aug 2022
- 2022Argumentative Explanations for Pattern-Based Text Classifiers22 May 2022
- 2021exp(ASPc) : Explaining ASP Programs with Choice Atoms and Constraint Rules17 Sep 2021
- 2021Argumentative XAI: A Survey24 May 2021
- 2021Generating explanations for answer set programming applications18 Apr 2021