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Enhancing Search-Based QBF Solving by Dynamic Blocked Clause Elimination

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Logic for Programming, Artificial Intelligence, and Reasoning (LPAR 2015)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9450))

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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.

Supported by the Austrian Science Fund (FWF) under grants S11408-N23 and S11409-N23.

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Notes

  1. 1.

    \(C'\) can also contain literals assigned by pure/unit literal detection, but as they are left to the maximal decision variable in the prefix, we treat them like decision variables.

  2. 2.

    http://lonsing.github.io/depqbf/.

  3. 3.

    http://qbf.satisfiability.org/gallery.

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Author information

Authors and Affiliations

  1. Knowledge-Based Systems Group, Vienna University of Technology, Vienna, Austria

    Florian Lonsing & Uwe Egly

  2. Department of Computer Science, University of Toronto, Toronto, Canada

    Fahiem Bacchus

  3. Institute for Formal Models and Verification, JKU Linz, Linz, Austria

    Armin Biere & Martina Seidl

Authors
  1. Florian Lonsing
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  2. Fahiem Bacchus
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  3. Armin Biere
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  4. Uwe Egly
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  5. Martina Seidl
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Corresponding author

Correspondence to Florian Lonsing .

Editor information

Editors and Affiliations

  1. New York University, New York, New York, USA

    Martin Davis

  2. University of the South Pacific, Suva, Fiji

    Ansgar Fehnker

  3. Macquarie University, Sydney, New South Wales, Australia

    Annabelle McIver

  4. The University of Manchester, Manchester, United Kingdom

    Andrei Voronkov

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Lonsing, F., Bacchus, F., Biere, A., Egly, U., Seidl, M. (2015). Enhancing Search-Based QBF Solving by Dynamic Blocked Clause Elimination. In: Davis, M., Fehnker, A., McIver, A., Voronkov, A. (eds) Logic for Programming, Artificial Intelligence, and Reasoning. LPAR 2015. Lecture Notes in Computer Science(), vol 9450. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-48899-7_29

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  • DOI: https://doi.org/10.1007/978-3-662-48899-7_29

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