Using ASP(Q) to Handle Inconsistent Prioritized Data

Fuente: arXiv
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Autori principali: Bienvenu, Meghyn, Bourgaux, Camille, Jean, Robin, Mazzotta, Giuseppe
Natura: Preprint
Pubblicazione: 2026
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author Bienvenu, Meghyn
Bourgaux, Camille
Jean, Robin
Mazzotta, Giuseppe
author_facet Bienvenu, Meghyn
Bourgaux, Camille
Jean, Robin
Mazzotta, Giuseppe
contents 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.
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id arxiv_https___arxiv_org_abs_2604_21603
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publishDate 2026
record_format arxiv
spellingShingle Using ASP(Q) to Handle Inconsistent Prioritized Data
Bienvenu, Meghyn
Bourgaux, Camille
Jean, Robin
Mazzotta, Giuseppe
Logic in Computer Science
Artificial Intelligence
Databases
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.
title Using ASP(Q) to Handle Inconsistent Prioritized Data
topic Logic in Computer Science
Artificial Intelligence
Databases
url https://arxiv.org/abs/2604.21603