Fast Set Bounds Propagation Using a BDD-SAT Hybrid

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    Author
    Gange, G; Stuckey, PJ; Lagoon, V
    Date
    2010-01-01
    Source Title
    Journal of Artificial Intelligence Research
    Publisher
    AI ACCESS FOUNDATION
    University of Melbourne Author/s
    Gange, Graeme; Stuckey, Peter; LAGOON, VITALY
    Affiliation
    Computer Science and Software Engineering
    Metadata
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    Document Type
    Journal Article
    Citations
    Gange, 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 Status
    This item is currently not available from this repository
    URI
    http://hdl.handle.net/11343/29302
    DOI
    10.1613/jair.3014
    Abstract
    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.
    Keywords
    Artificial Intelligence and Image Processing

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