Conflict-driven answer set solving: From theory to practice

We introduce an approach to computing answer sets of logic programs, based on concepts successfully applied in Satisfiability (SAT) checking. The idea is to view inferences in Answer Set Programming (ASP) as unit propagation on nogoods. This provides us with a uniform constraint-based framework capt...

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Bibliographic Details
Published in:Artificial intelligence Vol. 187-188; pp. 52 - 89
Main Authors: Gebser, Martin, Kaufmann, Benjamin, Schaub, Torsten
Format: Journal Article
Language:English
Published: Oxford Elsevier B.V 01.08.2012
Elsevier
Subjects:
Algorithms
Answer set programming
Applied sciences
Artificial intelligence
Computation
Computer science; control theory; systems
Exact sciences and technology
Expert systems
Learning and adaptive systems
Logic programming
Logical, boolean and switching functions
Nonmonotonic reasoning
Programming
Solvers
Theoretical computing
Versatility
Answer set programming
Nonmonotonic reasoning
Logic programming
Conflict resolution
Competitiveness
Knowledge representation
Algorithmics
Constraint satisfaction
Inference
Logical programming
Circumscription
Set theory
Satisfiability
ISSN:0004-3702, 1872-7921
Online Access:Get full text
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Summary:We introduce an approach to computing answer sets of logic programs, based on concepts successfully applied in Satisfiability (SAT) checking. The idea is to view inferences in Answer Set Programming (ASP) as unit propagation on nogoods. This provides us with a uniform constraint-based framework capturing diverse inferences encountered in ASP solving. Moreover, our approach allows us to apply advanced solving techniques from the area of SAT. As a result, we present the first full-fledged algorithmic framework for native conflict-driven ASP solving. Our approach is implemented in the ASP solver clasp that has demonstrated its competitiveness and versatility by winning first places at various solver contests.
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ISSN:0004-3702
1872-7921
DOI:10.1016/j.artint.2012.04.001