Semantical considerations on nonmonotonic logic
Artificial Intelligence
Is intractability of nonmonotonic reasoning a real drawback?
Artificial Intelligence
Verifying security protocols as planning in logic programming
ACM Transactions on Computational Logic (TOCL) - Special issue devoted to Robert A. Kowalski
Extending and implementing the stable model semantics
Artificial Intelligence
An A-Prolog Decision Support System for the Space Shuttle
PADL '01 Proceedings of the Third International Symposium on Practical Aspects of Declarative Languages
On the Expressibility of Stable Logic Programming
LPNMR '01 Proceedings of the 6th International Conference on Logic Programming and Nonmonotonic Reasoning
The USA-Advisor: A Case Study in Answer Set Planning
LPNMR '01 Proceedings of the 6th International Conference on Logic Programming and Nonmonotonic Reasoning
A Deductive System for Non-Monotonic Reasoning
LPNMR '97 Proceedings of the 4th International Conference on Logic Programming and Nonmonotonic Reasoning
Smodels - An Implementation of the Stable Model and Well-Founded Semantics for Normal LP
LPNMR '97 Proceedings of the 4th International Conference on Logic Programming and Nonmonotonic Reasoning
Here's the Beef: Answer Set Programming !
ICLP '08 Proceedings of the 24th International Conference on Logic Programming
Integrating answer set programming and constraint logic programming
Annals of Mathematics and Artificial Intelligence
Stable models and difference logic
Annals of Mathematics and Artificial Intelligence
Towards a Type Discipline for Answer Set Programming
Types for Proofs and Programs
ICLP '09 Proceedings of the 25th International Conference on Logic Programming
A Module-Based Framework for Multi-language Constraint Modeling
LPNMR '09 Proceedings of the 10th International Conference on Logic Programming and Nonmonotonic Reasoning
Theory and Practice of Logic Programming
Enhancing ASP systems for planning with temporal constraints
LPNMR'07 Proceedings of the 9th international conference on Logic programming and nonmonotonic reasoning
Integrating answer set reasoning with constraint solving techniques
FLOPS'08 Proceedings of the 9th international conference on Functional and logic programming
FLOPS'08 Proceedings of the 9th international conference on Functional and logic programming
A translational approach to constraint answer set solving
Theory and Practice of Logic Programming
A 25-year perspective on logic programming
A 25-year perspective on logic programming
Approximation of action theories and its application to conformant planning
Artificial Intelligence
Potassco: The Potsdam Answer Set Solving Collection
AI Communications - Answer Set Programming
Strong equivalence of logic programs with abstract constraint atoms
LPNMR'11 Proceedings of the 11th international conference on Logic programming and nonmonotonic reasoning
Industrial-size scheduling with ASP+CP
LPNMR'11 Proceedings of the 11th international conference on Logic programming and nonmonotonic reasoning
A semantic account for modularity in multi-language modelling of search problems
FroCoS'11 Proceedings of the 8th international conference on Frontiers of combining systems
Using answer set programming for the automatic compilation of assessment tests
ICLP'06 Proceedings of the 22nd international conference on Logic Programming
Macros, macro calls and use of ensembles in modular answer set programming
ICLP'06 Proceedings of the 22nd international conference on Logic Programming
Translation-based constraint answer set solving
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Three
Asp modulo csp: The clingcon system
Theory and Practice of Logic Programming
Inductive definitions in constraint programming
ACSC '13 Proceedings of the Thirty-Sixth Australasian Computer Science Conference - Volume 135
Relating constraint answer set programming languages and algorithms
Artificial Intelligence
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Answer set programming (ASP for short) is a declarative problem solving framework that has been recently attracting the attention of researchers for its expressiveness and for its well-engineered and optimized implementations. Still, state-of-the-art answer set solvers have huge memory requirements, because the ground instantiation of the input program must be computed before the actual reasoning starts. This prevents ASP to be effective on several classes of problems. In this paper we integrate answer set generation and constraint solving to reduce the memory requirements for a class of multi-sorted logic programs with cardinality constraints. We prove some theoretical results, introduce a provably sound and complete algorithm, and report experimental results showing that our approach can solve problem instances with significantly larger domains.