Artificial Intelligence
A filtering algorithm for constraints of difference in CSPs
AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
Knowledge compilation and theory approximation
Journal of the ACM (JACM)
Local and global relational consistency
Theoretical Computer Science - Special issue: principles and practice of constraint programming
Representation Selection for Constraint Satisfaction: A Case Study Using n-Queens
IEEE Expert: Intelligent Systems and Their Applications
Algorithms for Enumerating All Perfect, Maximum and Maximal Matchings in Bipartite Graphs
ISAAC '97 Proceedings of the 8th International Symposium on Algorithms and Computation
On the Satisfiability of Symmetrical Constrained Satisfaction Problems
ISMIS '93 Proceedings of the 7th International Symposium on Methodologies for Intelligent Systems
On Forward Checking for Non-binary Constraint Satisfaction
CP '99 Proceedings of the 5th International Conference on Principles and Practice of Constraint Programming
Constraint Processing
Constraint and Integer Programming: Toward a Unified Methodology (Operations Research/Computer Science Interfaces", 27)
Graphs and Hypergraphs
A constraint satisfaction approach to geospatial reasoning
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 1
Abstraction via approximate symmetry
IJCAI'93 Proceedings of the 13th international joint conference on Artifical intelligence - Volume 2
Towards a practical theory of reformulation for reasoning about physical systems
Artificial Intelligence - Special volume on reformulation
Artificial Intelligence: A Modern Approach
Artificial Intelligence: A Modern Approach
An end-to-end approach for QoS-aware service composition
EDOC'09 Proceedings of the 13th IEEE international conference on Enterprise Distributed Object Computing
Reformulating constraint models using input data
SARA'07 Proceedings of the 7th International conference on Abstraction, reformulation, and approximation
New methods for proving the impossibility to solve problems through reduction of problem spaces
Annals of Mathematics and Artificial Intelligence
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Constraint Programming is a powerful approach for modeling and solving many combinatorial problems, scalability, however, remains an issue in practice. Abstraction and reformulation techniques are often sought to overcome the complexity barrier. In this paper we introduce four reformulation techniques that operate on the various components of a Constraint Satisfaction Problem (CSP) in order to reduce the cost of problem solving and facilitate scalability. Our reformulations modify one or more component of the CSP (i.e., the query, variables domains, constraints) and detect symmetrical solutions to avoid generating them. We describe each of these reformulations in the context of CSPs, then evaluate their performance and effects in on the building identification problem introduced by Michalowski and Knoblock.