Q-Resolution with Generalized Axioms

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

Q-resolution is a proof system for quantified Boolean formulas (QBFs) in prenex conjunctive normal form (PCNF) which underlies search-based QBF solvers with clause and cube learning (QCDCL). With the aim to derive and learn stronger clauses and cubes earlier in the search, we generalize the axioms of the Q-resolution calculus resulting in an exponentially more powerful proof system. The generalized axioms introduce an interface of Q-resolution to any other QBF proof system allowing for the direct combination of orthogonal solving techniques. We implemented a variant of the Q-resolution calculus with generalized axioms in the QBF solver DepQBF. As two case studies, we apply integrated SAT solving and resource-bounded QBF preprocessing during the search to heuristically detect potential axiom applications. Experiments with application benchmarks indicate a substantial performance improvement.
Original languageEnglish
Title of host publicationTheory and Applications of Satisfiability Testing - SAT 2016 - 19th International Conference, Bordeaux, France, July 5-8, 2016
Editors Nadia Creignou, Daniel Le Berre
PublisherSpringer
Pages435-452
Number of pages18
Volume9710
DOIs
Publication statusPublished - 2016

Publication series

NameLecture Notes in Computer Science (LNCS)

Fields of science

  • 102 Computer Sciences
  • 102001 Artificial intelligence
  • 102011 Formal languages
  • 102022 Software development
  • 102031 Theoretical computer science
  • 603109 Logic
  • 202006 Computer hardware

JKU Focus areas

  • Computation in Informatics and Mathematics

Cite this