A System for Explainable Answer Set Programming
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Abstract (arXiv)
We present xclingo, a tool for generating explanations from ASP programs annotated with text and labels. These annotations allow tracing the application of rules or the atoms derived by them. The input of xclingo is a markup language written as ASP comment lines, so the programs annotated in this way can still be accepted by a standard ASP solver. xclingo translates the annotations into additional predicates and rules and uses the ASP solver clingo to obtain the extension of those auxiliary predicates. This information is used afterwards to construct derivation trees containing textual explanations. The language allows selecting which atoms to explain and, in its turn, which atoms or rules to include in those explanations. We illustrate the basic features through a diagnosis problem from the literature.
Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). First posted on arXiv 22 Sep 2020.
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Citing papers per year: 2021: 2; 2022: 1; 2023: 4; 2024: 1; 2025: 1; 2026: 1.
10 papers.
- 2021exp(ASPc) : Explaining ASP Programs with Choice Atoms and Constraint Rulescited by 3
- 2023An ASP Framework for the Refinement of Authorization and Obligation Policiescited by 3
- 2022Explanations as Programs in Probabilistic Logic Programmingcited by 2
- 2023Explanations for Answer Set Programmingcited by 1
- 2023Explainable Answer-set Programmingcited by 1
- 2024Explaining Explanations in Probabilistic Logic Programmingcited by 1
- 2021Explainable Machine Larning for liver transplantationcited by 0
- 2023Embracing Background Knowledge in the Analysis of Actual Causality: An Answer Set Programming Approachcited by 0
- 2025A Proof-of-Concept for Explainable Disease Diagnosis Using Large Language Models and Answer Set Programmingcited by 0
- 2026HyDI: A hybrid Deep Learning-Inductive Logic Programming ensemble for multi-label classificationcited by 0
- 2026HyDI: A hybrid Deep Learning-Inductive Logic Programming ensemble for multi-label classification29 Sep 2026
- 2025A Proof-of-Concept for Explainable Disease Diagnosis Using Large Language Models and Answer Set Programming30 Dec 2025
- 2024Explaining Explanations in Probabilistic Logic Programming30 Jan 2024
- 2023Explainable Answer-set Programming30 Aug 2023
- 2023Explanations for Answer Set Programming30 Aug 2023
- 2023Embracing Background Knowledge in the Analysis of Actual Causality: An Answer Set Programming Approach6 Jun 2023
- 2023An ASP Framework for the Refinement of Authorization and Obligation Policies22 May 2023
- 2022Explanations as Programs in Probabilistic Logic Programming6 Oct 2022
- 2021Explainable Machine Larning for liver transplantation28 Sep 2021
- 2021exp(ASPc) : Explaining ASP Programs with Choice Atoms and Constraint Rules17 Sep 2021