On the minimality and global consistency of row-convex constraint networks
Journal of the ACM (JACM)
Constraint satisfaction over connected row-convex constraints
Artificial Intelligence
Bucket elimination: a unifying framework for reasoning
Artificial Intelligence
Path Consistency on Triangulated Constraint Graphs
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
Consistency and set intersection
Eighteenth national conference on Artificial intelligence
Constraint Processing
Simple randomized algorithms for tractable row and tree convex constraints
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Making AC-3 an optimal algorithm
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 1
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We propose an algorithm for the class of connected row convex constraints. In this algorithm, we introduce a novel variable elimination method to solve the constraints. This method is simple and able to make use of the sparsity of the problem instances. One of its key operations is the composition of two constraints. We have identified several nice properties of connected row convex constraints. Those properties enable the development of a fast composition algorithm whose complexity is linear to the size of the variable domains. Compared with the existing work including randomized algorithms, the new algorithm has favorable worst case time and working space complexity. Experimental results also show a significant performance margin over the existing consistency based algorithms.