NEW RESEARCH LINES FOR MAX-SAT - Exploiting the Recent Resolution Rule for Max-SAT

Federico Heras

2010

Abstract

This paper presents the current state-of-the-art techniques for Max-SAT solving and points out new research lines in order to exploit the benefits of the novel resolution rule for Max-SAT.

References

  1. Argelich, J., Li, C. M., and Manyà, F. (2008). A preprocessor for max-sat solvers. In SAT, pages 15-20.
  2. Bonet, M. L., Levy, J., and Manyà, F. (2007). Resolution for max-sat. Artif. Intell., 171(8-9):606-618.
  3. Buresh-Oppenheim, J. and Mitchell, D. G. (2006). Minimum witnesses for unsatisfiable 2cnfs. In SAT, pages 42-47.
  4. Cha, B. and Iwama, K. (1996). Adding new clauses for faster local search. In Proc. of the 13thAAAI, pages 332-337, Portland, OR.
  5. Chu Min Li, F. M. and Planes, J. (2005). Exploiting unit propagation to compute lower bounds in branch and bound max-sat solvers. In Proc. of the 11th CP, Sitges, Spain.
  6. Eén, N. and Biere, A. (2005). Effective preprocessing in sat through variable and clause elimination. In SAT, pages 61-75.
  7. Heras, F. (2009). Max-sat resolution-based pre-processings and their effect on local search solvers. Submitted.
  8. Heras, F. and Larrosa, J. (2008). A max-sat inference-based pre-processing for max-clique. In SAT, pages 139- 152.
  9. Heras, F., Larrosa, J., and Oliveras, A. (2008). Minimaxsat: An efficient weighted max-sat solver. J. Artif. Intell. Res. (JAIR), 31:1-32.
  10. Larrosa, J., Heras, F., and de Givry, S. (2008). A logical approach to efficient max-sat solving. Artificial Intelligence, 172(2-3):204-233.
  11. Li, C. M., Manyà, F., and Planes, J. (2007). New inference rules for max-sat. J. Artif. Intell. Res. (JAIR), 30:321- 359.
  12. Liffiton, M. H. and Sakallah, K. A. (2008). Algorithms for computing minimal unsatisfiable subsets of constraints. J. Autom. Reasoning, 40(1):1-33.
  13. Lin, H., Su, K., and Li, C. M. (2008). Within-problem learning for efficient lower bound computation in max-sat solving. In AAAI, pages 351-356.
  14. Rish, I. and Dechter, R. (2000). Resolution versus search: Two strategies for sat. J. Autom. Reasoning, 24(1/2).
  15. Selman, B., Kautz, H. A., and Cohen, B. (1993). Local search strategies for satisfiability testing. In Proceedings of the second DIMACS Challenges on Cliques, Coloring and Satisfiability.
  16. Selman, B., Levesque, H. J., and Mitchell, D. G. (1992). A new method for solving hard satisfiability problems. In AAAI, pages 440-446.
  17. Silva, J. P. M. and Sakallah, K. A. (1996). Grasp - a new search algorithm for satisfiability. In ICCAD, pages 220-227.
  18. Xu, K., Boussemart, F., Hemery, F., and Lecoutre, C. (2007). Random constraint satisfaction: Easy generation of hard (satisfiable) instances. Artif. Intell., 171(8-9):514-534.
  19. 1Available at http://www.nlsde.buaa.edu.cn/ kexu/
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Paper Citation


in Harvard Style

Heras F. (2010). NEW RESEARCH LINES FOR MAX-SAT - Exploiting the Recent Resolution Rule for Max-SAT . In Proceedings of the 2nd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART, ISBN 978-989-674-021-4, pages 648-651. DOI: 10.5220/0002761706480651


in Bibtex Style

@conference{icaart10,
author={Federico Heras},
title={NEW RESEARCH LINES FOR MAX-SAT - Exploiting the Recent Resolution Rule for Max-SAT},
booktitle={Proceedings of the 2nd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,},
year={2010},
pages={648-651},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002761706480651},
isbn={978-989-674-021-4},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 2nd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,
TI - NEW RESEARCH LINES FOR MAX-SAT - Exploiting the Recent Resolution Rule for Max-SAT
SN - 978-989-674-021-4
AU - Heras F.
PY - 2010
SP - 648
EP - 651
DO - 10.5220/0002761706480651