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    block this user Domagoj Babic Trusted member

    Research Associate

    UC Berkeley
    University of British Columbia
    Microsoft Research

    Integration of Supercubing and Learning in a SAT Solver

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    Learning is an essential pruning technique in modern SAT solvers, but it exploits a relatively small amount of information that can be deduced from the conflicts. Recently a new pruning technique called supercubing was proposed [1]. Supercubing can exploit functional symmetries that are abundant in industrial SAT instances. We point out the significant difficulties of integrating supercubing with learning and propose solutions. Our experimental solver is the first supercubing-based solver with performance comparable to leading edge solvers.

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    Description

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    Title : Integration of Supercubing and Learning in a SAT Solver
    Author(s) : Domagoj Babic, Alan J. Hu
    Abstract : Learning is an essential pruning technique in modern SAT solvers, but it exploits a relatively small amount of information that can be deduced from the conflicts. Recently a new pruning technique called supercubing was proposed [1]. Supercubing can exploit functional symmetries that are abundant in industrial SAT instances. We point out the significant difficulties of integrating supercubing with learning and propose solutions. Our experimental solver is the first supercubing-based solver with performance comparable to leading edge solvers.
    Keywords : propositional satisfiability, SAT, boolean satisfiability, search space pruning

    Subject : unspecified
    Area : Computer Science
    Language : English
    Year : 2005

    Affiliations :  University of British Columbia
    Conference_title : ASP-DAC'05: Proceedings of the 2005 conference on Asia South Pacific design automation
    Publisher : ACM
    Pages : 438--444
    Url : http://www.domagoj-babic.com/uploads/Pubs/ASPDAC05/aspdac05.pdf
    Doi : http://doi.acm.org/10.1145/1120725.1120908

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