Fast Set Bounds Propagation Using a BDD-SAT Hybrid
AuthorGange, G; Stuckey, PJ; Lagoon, V
Source TitleJournal of Artificial Intelligence Research
PublisherAI ACCESS FOUNDATION
AffiliationComputer Science and Software Engineering
Document TypeJournal Article
CitationsGange, G., Stuckey, P. J. & Lagoon, V. (2010). Fast Set Bounds Propagation Using a BDD-SAT Hybrid. JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH, 38, pp.307-338. https://doi.org/10.1613/jair.3014.
Access StatusThis item is currently not available from this repository
Binary Decision Diagram (BDD) based set bounds propagation is a powerful approach to solving set-constraint satisfaction problems. However, prior BDD based techniques in- cur the significant overhead of constructing and manipulating graphs during search. We present a set-constraint solver which combines BDD-based set-bounds propagators with the learning abilities of a modern SAT solver. Together with a number of improvements beyond the basic algorithm, this solver is highly competitive with existing propagation based set constraint solvers.
KeywordsArtificial Intelligence and Image Processing
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