Decomposing constraint satisfaction problems using database techniques
Artificial Intelligence
On the Structure of Armstrong Relations for Functional Dependencies
Journal of the ACM (JACM)
Consistency restoriation and explanations in dynamic CSPs----application to configuration
Artificial Intelligence
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
When Two Case Bases Are Better than One: Exploiting Multiple Case Bases
ICCBR '01 Proceedings of the 4th International Conference on Case-Based Reasoning: Case-Based Reasoning Research and Development
Constraint Programming Lessons Learned from Crossword Puzzles
AI '01 Proceedings of the 14th Biennial Conference of the Canadian Society on Computational Studies of Intelligence: Advances in Artificial Intelligence
Evaluating compound critiquing recommenders: a real-user study
Proceedings of the 8th ACM conference on Electronic commerce
A fast arc consistency algorithm for n-ary constraints
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 1
Data structures for generalised arc consistency for extensional constraints
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
A compression algorithm for large arity extensional constraints
CP'07 Proceedings of the 13th international conference on Principles and practice of constraint programming
Generalized arc consistency for positive table constraints
CP'06 Proceedings of the 12th international conference on Principles and Practice of Constraint Programming
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Constraints that are defined by tables of allowed tuples of assignments are common in constraint programming. In this paper we present an approach to reformulating table constraints of large arity into a conjunction of lower arity constraints. Our approach exploits functional dependencies. We study the complexity of finding reformulations that either minimize the memory size or arity of a constraint using a set of its functional dependencies. We also present an algorithm to compute such reformulations. We show that our technique is complementary to existing approaches for compressing extensional constraints.