Logic for Programming, Artificial Intelligence, and Reasoning

Logic for Programming, Artificial Intelligence, and Reasoning pp 418-433 | Cite as

Enhancing Search-Based QBF Solving by Dynamic Blocked Clause Elimination

  • Florian Lonsing
  • Fahiem Bacchus
  • Armin Biere
  • Uwe Egly
  • Martina Seidl
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9450)

Abstract

Among preprocessing techniques for quantified Boolean formula (QBF) solving, quantified blocked clause elimination (QBCE) has been found to be extremely effective. We investigate the power of dynamically applying QBCE in search-based QBF solving with clause and cube learning (QCDCL). This dynamic application of QBCE is in sharp contrast to its typical use as a mere preprocessing technique. In our dynamic approach, QBCE is applied eagerly to the formula interpreted under the assignments that have been enumerated in QCDCL. The tight integration of QBCE in QCDCL results in a variant of cube learning which is exponentially stronger than the traditional method. We implemented our approach in the QBF solver DepQBF and ran experiments on instances from the QBF Gallery 2014. On application benchmarks, QCDCL with dynamic QBCE substantially outperforms traditional QCDCL. Moreover, our approach is compatible with incremental solving and can be combined with preprocessing techniques other than QBCE.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • Florian Lonsing
    • 1
  • Fahiem Bacchus
    • 2
  • Armin Biere
    • 3
  • Uwe Egly
    • 1
  • Martina Seidl
    • 3
  1. 1.Knowledge-Based Systems GroupVienna University of TechnologyViennaAustria
  2. 2.Department of Computer ScienceUniversity of TorontoTorontoCanada
  3. 3.Institute for Formal Models and VerificationJKU LinzLinzAustria

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