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The EZSMT Solver: Constraint Answer Set Solving meets SMT

Posted on:2017-01-22Degree:M.SType:Thesis
University:University of Nebraska at OmahaCandidate:Susman, BenjaminFull Text:PDF
GTID:2448390005460402Subject:Artificial Intelligence
Abstract/Summary:
Constraint answer set programming is a promising research direction that integrates answer set programming with constraint processing. It is often informally related to the field of Satisfiability Modulo Theories. Yet, the exact formal link is obscured as the terminology and concepts used in these two research areas differ. In this thesis, by connecting these two areas, we begin the cross-fertilization of not only of the theoretical foundations of both areas but also of the existing solving technologies. We present the system EZSMT, one of the first solvers of this nature, which is able to take a large class of constraint answer set programs and rewrite them into Satisfiability Modulo Theories programs so that Satisfiability Modulo Theories technology can be used to process these programs.
Keywords/Search Tags:Answer set, Satisfiability modulo theories, Constraint
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