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Mathematical Problems in Engineering
Volume 2013, Article ID 165927, 6 pages
http://dx.doi.org/10.1155/2013/165927
Research Article

Message Passing Algorithm for Solving QBF Using More Reasoning

School of Computer Science and Information Technology, Northeast Normal University, Changchun 130117, China

Received 26 June 2013; Accepted 24 July 2013

Academic Editor: William Guo

Copyright © 2013 Su Weihua et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. J. Rintanen, “Asymptotically optimal encodings of conformant planning in QBF,” in Proceedings of the 22nd AAAI Conference on Artificial Intelligence, pp. 1045–1050, July 2007. View at Scopus
  2. P. Marin, C. Miller, and B. Becker, “Incremental QBF preprocessing for partial design verification,” in Proceeding of the 15th International Conference of Theory and Applications of Satisfiability Testing, pp. 473–474, 2012.
  3. U. Egly, T. Eiter, H. Tompits, and S. Woltran, “Solving advanced reasoning tasks using quantified Boolean formulas,” in Proceeding of the 12th AAAI Conference on Artificial Intelligence, pp. 417–422, 2000.
  4. G. Pan and M. Y. Vardi, “Optimizing a BDD-based modal solver,” in Proceedings of the 19th International Conference on Automated Deduction, pp. 75–89, August 2003. View at Scopus
  5. I. P. Gent, H. H. Hoos, A. G. D. Rowley, and K. Smyth, “Using stochastic local search to solve quantified Boolean formulae,” in Proceeding of the Principles and Practice of Constraint Programming, pp. 348–362, 2003.
  6. I. Gent, E. Giunchiglia, M. Narizzano, A. Rowley, and A. Tachella, “Watched data structures for QBF solvers,” in Proceeding of the 6th International Conference on Theory and Applications of Satisfiability Testing, pp. 348–355, 2003.
  7. E. Giunchiglia, M. Narizzano, and A. Tacchella, “QuBE: a system for deciding quantified Boolean formulas satisfiability,” in Proceeding of the 17th International Joint Conference on Artificial Intelligence, pp. 18–23, 2001.
  8. J. Rintanen, “Partial implicit unfolding in the Davis Putnam procedure for quantified Boolean formulae,” in Proceeding of the 8th International Conference on Logic for Programming, Artificial Intelligence and Reasoning, pp. 362–376, 2001.
  9. L. Zhang and S. Malik, “Towards a symmetric treatment of satisfaction and conflicts in quantified Boolean formula evaluation,” in Proceeding of the Principles and Practice of Constraint Programming, pp. 200–215, 2002.
  10. F. Bacchus, “Enhancing Davis Putnam with extended binary clause reasoning,” in Proceedings of the 18th National Conference on Artificial Intelligence (AAAI '02), pp. 613–619, August 2002. View at Scopus
  11. M. Mézard, G. Parisi, and R. Zecchina, “Analytic and algorithmic solution of random satisfiability problems,” Science, vol. 297, no. 5582, pp. 812–815, 2002. View at Publisher · View at Google Scholar · View at Scopus