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arxiv: 1108.5837 · v1 · pith:UC2KY5VGnew · submitted 2011-08-30 · 💻 cs.AI · cs.LO

Translating Answer-Set Programs into Bit-Vector Logic

classification 💻 cs.AI cs.LO
keywords answerlogicprogramssetsanswer-setbit-vectorcomputingdifference
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Answer set programming (ASP) is a paradigm for declarative problem solving where problems are first formalized as rule sets, i.e., answer-set programs, in a uniform way and then solved by computing answer sets for programs. The satisfiability modulo theories (SMT) framework follows a similar modelling philosophy but the syntax is based on extensions of propositional logic rather than rules. Quite recently, a translation from answer-set programs into difference logic was provided---enabling the use of particular SMT solvers for the computation of answer sets. In this paper, the translation is revised for another SMT fragment, namely that based on fixed-width bit-vector theories. Thus, even further SMT solvers can be harnessed for the task of computing answer sets. The results of a preliminary experimental comparison are also reported. They suggest a level of performance which is similar to that achieved via difference logic.

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