On Expansion and Resolution in CEGAR Based QBF Solving

03/26/2018 ∙ by Leander Tentrup, et al. ∙ 0

A quantified Boolean formula (QBF) is a propositional formula extended with universal and existential quantification over propositions. There are two methodologies in CEGAR based QBF solving techniques, one that is based on a refinement loop that builds partial expansions and a more recent one that is based on the communication of satisfied clauses. Despite their algorithmic similarity, their performance characteristics in experimental evaluations are very different and in many cases orthogonal. We compare those CEGAR approaches using proof theory developed around QBF solving and present a unified calculus that combines the strength of both approaches. Lastly, we implement the new calculus and confirm experimentally that the theoretical improvements lead to improved performance.



There are no comments yet.


page 1

page 2

page 3

page 4

This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.