Building structure into local search for SAT

IJCAI International Joint Conference on Artificial Intelligence

Volumn , Issue , 2007, Pages 2359-2364

  Pham, Duc Nghia ^a,b   Thornton, John ^a,b   Sattar, Abdul ^a,b  

^a CSIRO   (Australia)

^b GRIFFITH UNIVERSITY   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

BENCH-MARK PROBLEMS; DEPENDENT VARIABLES; EXPERIMENTAL STUDIES; INDEPENDENT VARIABLES; LOCAL SEARCH TECHNIQUES; SATISFIABILITY PROBLEMS; STRUCTURED PROBLEMS; VARIABLE DEPENDENCIES;

ARTIFICIAL INTELLIGENCE;

INFORMATION ANALYSIS;

EID: 84880913380     PISSN: 10450823     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (14)

1. th Design Automation Conference (DAC-02), pages 731-736, 2002.
2. Ramoón Béjar and Felip Manyà. Solving the round robin problem using propositional logic. In Proceedings of the Seventeenth National Conference on Artificial Intelligence (AAAI-00), pages 262-266, 2000.
3. Niklas Eén and Armin Biere. Effective preprocessing in SAT through variable and clause elimination. In Proceedings of the Eighth International Conference on Theory and Applications of Satisfiability Testing (SAT-05), pages 61-75, 2005.
4. Holger H. Hoos. An adaptive noise mechanism for WalkSAT. In Proceedings of the Eighteenth National Conference on Artificial Intelligence (AAAI-02), pages 635-660, 2002.
5. Frank Hutter, Dave A. D. Tompkins, and Holger H. Hoos. Scaling and probabilistic smoothing: Efficient dynamic local search for SAT. In Proceedings of the Eighth International Conference on Principles and Practice of Constraint Programming (CP-02), pages 233-248, 2002.
6. Henry Kautz and Bart Selman. Pushing the envelope: Planning, propositional logic, and stochastic search. In Proceedings of the Thirteenth National Conference on Artificial Intelligence (AAAI-96), pages 1194-1201, 1996.
7. Richard Ostrowski, Éric Grégoire, Bertrand Mazure, and Lakhdar Saïs. Recovering and exploiting strutural knowledge from CNF formulas. In Proceedings of the Eighth International Conference on Principles and Practice of Constraint Programming (CP-02), pages 185-199, 2002.
8. Duc Nghia Pham, John Thornton, Abdul Sattar, and Adelraouf Ishtaiwi. SAT-based versus CSP-based constraint weighting for satisfiability. In Proceedings of the Twentieth National Conference on Artificial Intelligence (AAAI-05), pages 455-460, 2005.
9. Bart Selman, Hector Levesque, and David Mitchell. A new method for solving hard satisfiability problems. In Proceedings of the Tenth National Conference on Artificial Intelligence (AAAI-92), pages 440-446, 1992.
10. Bart Selman, Henry Kautz, and David McAllester. Ten challenges in propositional reasoning and search. In Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence (IJCAI-97), pages 50-54, 1997.
11. John Thornton, Duc Nghia Pham, Stuart Bain, and Valnir Ferreira Jr. Additive versus multiplicative clause weighting for SAT. In Proceedings of the Twentieth National Conference on Artificial Intelligence (AAAI- 04), pages 191-196, 2004.
12. Dave A. D. Tompkins and Holger H. Hoos. UBCSAT: An implementation and experimentation environment for SLS algorithms for SAT and MAX-SAT. In SAT (Selected Papers), pages 306-320, 2004.
13. Benjamin W. Wah and Zhe Wu. Penalty formulations and trap-avoidance strategies for solving hard satisfiability problems. J. Comput. Sci. Technol., 20(1):3-17, 2005.
14. Lintao Zhang, Conor Madigan, Matthew Moskewicz, and Sharad Malik. Efficient conflict driven learning in a Boolean satisfiability solver. In Proceedings of the International Conference on Computer-Aided Design, pages 279-285, 2001.