AAS 390 Chapter Notes - Chapter 1: Answer Set Programming, Constraint Satisfaction Problem, Ios Press

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University of potsdam, manju@cs. uni-potsdam. de: clasp (2. 0. 6, application: Authors: gebser (university of potsdam), kaufmann, and t. schaub clasp1 combines the high-level modeling capacities of an- swer set programming (asp; [1]) with state-of-the-art tech- niques from the area of boolean constraint solving. It is originally designed and optimized for con ict-driven asp solving [2], [3], [4]. Most of its innovative algorithms and data structures, like e. g. asp-oriented pre-processing [5] or native support of aggregates [6], are thus outside the scope of sat solving. However, given the proximity of asp to sat, clasp can also deal with formulas in cnf via an additional dimacs frontend. As such, it can be viewed as a chaff-type boolean constraint solver [7] featuring a number of techniques found in sat solvers based on con ict-driven clause learning. For example, clasp supports pre-processing [8], [9], phase caching [10], on-the- y subsumption [11], and aggressive deletion [12].

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