Towards a theory of declarative knowledge
Foundations of deductive databases and logic programming
The well-founded semantics for general logic programs
Journal of the ACM (JACM)
Theoretical Computer Science
Proceedings of the 1999 international conference on Logic programming
Extending and implementing the stable model semantics
Artificial Intelligence
Nested expressions in logic programs
Annals of Mathematics and Artificial Intelligence
Logic programs with stable model semantics as a constraint programming paradigm
Annals of Mathematics and Artificial Intelligence
Theory and Practice of Logic Programming
ASSAT: computing answer sets of a logic program by SAT solvers
Artificial Intelligence - Special issue on nonmonotonic reasoning
Weight constraints as nested expressions
Theory and Practice of Logic Programming
The DLV system for knowledge representation and reasoning
ACM Transactions on Computational Logic (TOCL)
Answer Set Programming Based on Propositional Satisfiability
Journal of Automated Reasoning
Stable models and difference logic
Annals of Mathematics and Artificial Intelligence
Computing Stable Models via Reductions to Difference Logic
LPNMR '09 Proceedings of the 10th International Conference on Logic Programming and Nonmonotonic Reasoning
The Conflict-Driven Answer Set Solver clasp: Progress Report
LPNMR '09 Proceedings of the 10th International Conference on Logic Programming and Nonmonotonic Reasoning
The Second Answer Set Programming Competition
LPNMR '09 Proceedings of the 10th International Conference on Logic Programming and Nonmonotonic Reasoning
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
CMODELS: SAT-based disjunctive answer set solver
LPNMR'05 Proceedings of the 8th international conference on Logic Programming and Nonmonotonic Reasoning
Conflict-driven answer set solving: From theory to practice
Artificial Intelligence
Tableau Calculi for Logic Programs under Answer Set Semantics
ACM Transactions on Computational Logic (TOCL)
Hi-index | 0.00 |
Propositional satisfiability (SAT) solvers provide a promising computational platform for logic programs under the stable model semantics. Computing stable models of a logic program using a SAT solver presumes translating the program into a set of clauses in the DIMACS format which is accepted by most SAT solvers as input. In this paper, we present succinct translations from programs with choice rules, cardinality rules, and weight rules--also known as SMODELS programs--to sets of clauses. These translations enable us to harness SAT solvers as black boxes to the task of computing stable models for logic programs generated by any SMODELS compatible grounder such as LPARSE or GRINGO. In the experimental part of this paper, we evaluate the potential of SAT solver technology in finding stable models using NP-complete benchmark problems employed in the Second Answer Set Programming Competition.