Using ASP(Q) to Handle Inconsistent Prioritized Data
Abstract
We explore the use of answer set programming (ASP) and its extension with quantifiers, ASP(Q), for inconsistency-tolerant querying of prioritized data, where a priority relation between conflicting facts is exploited to define three notions of optimal repairs (Pareto-, globally- and completion-optimal). We consider the variants of three well-known semantics (AR, brave and IAR) that use these optimal repairs, and for which query answering is in the first or second level of the polynomial hierarchy for a large class of logical theories. Notably, this paper presents the first implementation of globally-optimal repair-based semantics, as well as the first implementation of the grounded semantics, which is a tractable under-approximation of all these optimal repair-based semantics. Our experimental evaluation sheds light on the feasibility of computing answers under globally-optimal repair semantics and the impact of adopting different semantics, approximations, and encodings.
Cite
@article{arxiv.2604.21603,
title = {Using ASP(Q) to Handle Inconsistent Prioritized Data},
author = {Meghyn Bienvenu and Camille Bourgaux and Robin Jean and Giuseppe Mazzotta},
journal= {arXiv preprint arXiv:2604.21603},
year = {2026}
}
Comments
This is an extended version of a paper appearing at the 23rd International Conference on Principles of Knowledge Representation and Reasoning (KR 2026). 21 pages