The paper presents a new look-ahead scheme for backtracking search for solving constraint satisfaction problems. This look-ahead scheme computes a heuristic for value ordering and domain pruning. The heuristic is based on approximating the number of solutions extending each partial solution. In particular, we investigate a recent partition-based approximation of tree-clustering algorithms, Iterative Join-Graph Propagation (IJGP), which belongs to the class of belief propagation algorithms that attracted substantial interest due to their success for probabilistic inference. Our empirical evaluation demonstrates that the counting-based heuristic approximated by IJGP yields a scalable, focused search. © Springer-Verlag Berlin Heidelberg 2004.
CITATION STYLE
Kask, K., Dechter, R., & Gogate, V. (2004). Counting-based look-ahead schemes for constraint satisfaction. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 3258, 317–331. https://doi.org/10.1007/978-3-540-30201-8_25
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