Using ASP(Q) to Handle Inconsistent Prioritized Data

TL;DR

This paper investigates using ASP(Q) for inconsistency-tolerant querying of prioritized data, introducing new semantics and implementations, and evaluating their computational feasibility.

Contribution

It presents the first implementation of globally-optimal repair semantics and grounded semantics for ASP(Q), with experimental analysis of their practicality.

Findings

First implementation of globally-optimal repair-based semantics.

First implementation of grounded semantics as a tractable approximation.

Experimental results on the feasibility of computing answers under these semantics.

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.