@article{AlvianoDJMP:TPLP2018,
title = {Cautious Reasoning in {ASP} via Minimal Models and Unsatisfiable Cores},
author = {Mario Alviano and Carmine Dodaro and Matti J\"arvisalo
and Marco Maratea and Alessandro Previti},
journal = {Theory and Practice of Logic Programming},
volume = {18},
number = {3--4},
pages = {319--336},
year = {2018},
}
Abstract:
Answer Set Programming (ASP) is a logic-based knowledge representation framework,
supporting---among other reasoning modes---the central task of query answering.
In the propositional case, query answering amounts to computing cautious consequences
of the input program among the atoms in a given set of candidates, where a cautious
consequence is an atom belonging to all stable models. Currently, the most efficient
algorithms either iteratively verify the existence of a stable model of the input
program extended with the complement of one candidate, where the candidate is
heuristically selected, or introduce a clause enforcing the falsity of at least one
candidate, so that the solver is free to choose which candidate to falsify at any
time during the computation of a stable model. This paper introduces new algorithms
for the computation of cautious consequences, with the aim of driving the solver to
search for stable models discarding more candidates. Specifically, one of such
algorithms enforces minimality on the set of true candidates, where different
notions of minimality can be used, and another takes advantage of unsatisfiable cores
computation. The algorithms are implemented in \textsc{wasp}, and experiments on
benchmarks from the latest ASP competitions show that the new algorithms perform
better than the state of the art.