AIGSolve
The QBF solver AIGSolve. AIGSolve is a rewriting-based solver based on And-Inverter Graphs (AIGs). In this approach, quantifiers are eliminated, starting with the inner-most quantifiers. Intermediate results are represented symbolically using AIGs [22, 23]. The basic method consists of cofactorbased quantifier elimination which is combined with a multitude of optimization approaches including a SATand BDD-based compaction of the representations, methods for preprocessing QBF-formulas based on incremental SAT, heuristics that exchange quantifiers of the same level, heuristics that use BDD-based quantifier elimination as an alternative, as well as structure extraction and structure exploitation for the processed instances
References in zbMATH (referenced in 2 articles )
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- Peitl, Tomáš; Slivovsky, Friedrich; Szeider, Stefan: Dependency learning for QBF (2017)