Explanations for Answer Set Programming

TL;DR

This paper introduces xASP2, an enhanced system for generating explanation graphs in Answer Set Programming, supporting more constructs and providing concise, DAG-based explanations for broader ASP fragments.

Contribution

The paper extends xASP to support additional clingo constructs like choice rules, constraints, and aggregates, formalizing an explainable AI system for ASP.

Findings

Supports choice rules, constraints, and aggregates in explanations

Produces minimal assumption sets in explanation graphs

Formalizes an explainable AI framework for ASP

Abstract

The paper presents an enhancement of xASP, a system that generates explanation graphs for Answer Set Programming (ASP). Different from xASP, the new system, xASP2, supports different clingo constructs like the choice rules, the constraints, and the aggregates such as #sum, #min. This work formalizes and presents an explainable artificial intelligence system for a broad fragment of ASP, capable of shrinking as much as possible the set of assumptions and presenting explanations in terms of directed acyclic graphs.