Artificial Intelligence - Special issue on knowledge representation
Extending the Smodels system with cardinality and weight constraints
Logic-based artificial intelligence
Answer set based design of knowledge systems
Annals of Mathematics and Artificial Intelligence
CR-MODELS: an inference engine for CR-Prolog
LPNMR'07 Proceedings of the 9th international conference on Logic programming and nonmonotonic reasoning
Towards an integration of answer set and constraint solving
ICLP'05 Proceedings of the 21st international conference on Logic Programming
Here's the Beef: Answer Set Programming !
ICLP '08 Proceedings of the 24th International Conference on Logic Programming
Answer Set Programming with Constraints Using Lazy Grounding
ICLP '09 Proceedings of the 25th International Conference on Logic Programming
ICLP '09 Proceedings of the 25th International Conference on Logic Programming
Present and Future Challenges for ASP Systems
LPNMR '09 Proceedings of the 10th International Conference on Logic Programming and Nonmonotonic Reasoning
Making Your Hands Dirty Inspires Your Brain! Or How to Switch ASP into Production Mode
LPNMR '09 Proceedings of the 10th International Conference on Logic Programming and Nonmonotonic Reasoning
Theory and Practice of Logic Programming
A translational approach to constraint answer set solving
Theory and Practice of Logic Programming
Potassco: The Potsdam Answer Set Solving Collection
AI Communications - Answer Set 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
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The paper introduces a collection of knowledge representation languages, ν(C), parametrised over a class C of constraints. ν(C) is an extension of both CR-Prolog and CASP allowing the separation of a program into two parts: a regular program of CR-Prolog and a collection of denials whose bodies contain constraints from C with variables ranging over large domains. We study an instance AC0 from this family where C is a collection of constraints of the form X - Y K. We give brief implementation details of an algorithm computing the answer sets of programs of AC0 which does not ground constraint variables and tightly couples the "classical" ASP algorithm with an algorithm checking consistency of difference constraints. We present several examples to show the methodology of representing knowledge in AC0. The work makes it possible to solve problems which could not be solved by pure ASP or constraint solvers.