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Anytime answer set optimization via unsatisfiable core shrinking

Published online by Cambridge University Press:  14 October 2016

MARIO ALVIANO  and
CARMINE DODARO Open the ORCID record for CARMINE DODARO [Opens in a new window]
MARIO ALVIANO
Affiliation:
Department of Mathematics and Computer Science, University of Calabria, Italy (e-mail: [email protected], [email protected])
CARMINE DODARO
Affiliation:
Department of Mathematics and Computer Science, University of Calabria, Italy (e-mail: [email protected], [email protected])
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Abstract

Unsatisfiable core analysis can boost the computation of optimum stable models for logic programs with weak constraints. However, current solvers employing unsatisfiable core analysis either run to completion, or provide no suboptimal stable models but the one resulting from the preliminary disjoint cores analysis. This drawback is circumvented here by introducing a progression based shrinking of the analyzed unsatisfiable cores. In fact, suboptimal stable models are possibly found while shrinking unsatisfiable cores, hence resulting into an anytime algorithm. Moreover, as confirmed empirically, unsatisfiable core analysis also benefits from the shrinking process in terms of solved instances.

Keywords

answer set programmingweak constraintsunsatisfiable cores
Type
Regular Papers
Information
Theory and Practice of Logic Programming , Volume 16 , Special Issue 5-6: 32nd International Conference on Logic Programming , September 2016 , pp. 533 - 551
Copyright
Copyright © Cambridge University Press 2016 

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