The well-founded semantics for general logic programs
Journal of the ACM (JACM)
Stable models and non-determinism in logic programs with negation
PODS '90 Proceedings of the ninth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
A machine program for theorem-proving
Communications of the ACM
Efficient conflict driven learning in a boolean satisfiability solver
Proceedings of the 2001 IEEE/ACM international conference on Computer-aided design
ASSAT: computing answer sets of a logic program by SAT solvers
Eighteenth national conference on Artificial intelligence
Conflict Analysis in Search Algorithms for Satisfiability
ICTAI '96 Proceedings of the 8th International Conference on Tools with Artificial Intelligence
ASSAT: computing answer sets of a logic program by SAT solvers
Artificial Intelligence - Special issue on nonmonotonic reasoning
Answer set programming with clause learning
Answer set programming with clause learning
A backjumping technique for disjunctive logic programming
AI Communications
Answer Set Programming Based on Propositional Satisfiability
Journal of Automated Reasoning
ICLP '08 Proceedings of the 24th International Conference on Logic Programming
Fast SAT-based answer set solver
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
What is answer set programming?
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 3
Conflict-driven answer set solving
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
A model-theoretic counterpart of loop formulas
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
On the relation between answer set and sat procedures (or, between cmodels and smodels)
ICLP'05 Proceedings of the 21st international conference on Logic Programming
Tableau calculi for answer set programming
ICLP'06 Proceedings of the 22nd international conference on Logic Programming
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)
Relating constraint answer set programming languages and algorithms
Artificial Intelligence
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Nieuwenhuis et al. (2006. Solving SAT and SAT modulo theories: From an abstract Davis-Putnam-Logemann-Loveland procedure to DPLL(T). Journal of the ACM 53(6), 937977 showed how to describe enhancements of the Davis???Putnam???Logemann???Loveland algorithm using transition systems, instead of pseudocode. We design a similar framework for several algorithms that generate answer sets for logic programs: smodels, smodelscc, asp-sat with Learning (cmodels), and a newly designed and implemented algorithm sup. This approach to describe answer set solvers makes it easier to prove their correctness, to compare them, and to design new systems.