# exp(ASPc) : Explaining ASP Programs with Choice Atoms and Constraint Rules

arXiv: https://arxiv.org/abs/2109.08292 · HTML: https://mlsanity.com/paper/2109.08292/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 5 of its 18 references that are in the map.
- First posted on arXiv 17 Sep 2021.

## Builds on (most cited first, 5 of 5)

- [Justifying Answer Sets using Argumentation](https://mlsanity.com/paper/1411.5635/) (2014)
- [A System for Explainable Answer Set Programming](https://mlsanity.com/paper/2009.10242/) (2020)
- [Stepwise Debugging of Answer-Set Programs](https://mlsanity.com/paper/1705.06564/) (2017)
- [Justifications for Programs with Disjunctive and Causal-choice Rules](https://mlsanity.com/paper/1608.00870/) (2016)
- [Generating explanations for answer set programming applications](https://mlsanity.com/paper/2104.08963/) (2021)

## Built on by (most cited first, 3 of 3)

- [Explanations for Answer Set Programming](https://mlsanity.com/paper/2308.15879/) (2023)
- [Explainable Answer-set Programming](https://mlsanity.com/paper/2308.15901/) (2023)
- [An XAI View on Explainable ASP: Methods, Systems, and Perspectives](https://mlsanity.com/paper/2601.14764/) (2026)

## Abstract (arXiv)

We present an enhancement of exp(ASP), a system that generates explanation graphs for a literal l - an atom a or its default negation ~a - given an answer set A of a normal logic program P, which explain why l is true (or false) given A and P. The new system, exp(ASPc), differs from exp(ASP) in that it supports choice rules and utilizes constraint rules to provide explanation graphs that include information about choices and constraints.