Failed Literal Detection for QBF

  • Florian Lonsing
  • , Armin Biere

Research output: Chapter in Book/Report/Conference proceedingConference proceedingspeer-review

Abstract

Failed literal detection (FL) in SAT is a powerful approach for preprocessing. The basic idea is to assign a variable as assumption. If boolean constraint propagation (BCP) yields an empty clause then the negated assumption is necessary for satisfiability. Whereas FL is common in SAT, it cannot easily be applied to QBF due to universal quantification. We present two approaches for FL to preprocess prenex CNFs. The first one is based on abstraction where certain universal variables are treated as existentially quantified. Second we combine QBF-specific BCP (QBCP) in FL with Q-resolution to validate assignments learnt by FL. Finally we compare these two approaches to a third common approach based on SAT. It turns out that the three approaches are incomparable. Experimental evaluation demonstrates that FL for QBF can improve the performance of search- and elimination-based QBF solvers.
Original languageEnglish
Title of host publicationProc. 14th Intl. Conf. on Theory and Applications of Satisfiability Testing (SAT'11)
PublisherSpringer
Pages259-272
Number of pages14
Volume6695
ISBN (Print)9783642215803
DOIs
Publication statusPublished - Jun 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6695 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Fields of science

  • 102011 Formal languages
  • 102 Computer Sciences
  • 101 Mathematics

JKU Focus areas

  • Computation in Informatics and Mathematics

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