Pool resolution and its relation to regular resolution and DPLL with clause learning

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 3835 LNAI, Issue , 2005, Pages 580-594

  Van Gelder, Allen ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

POLYNOMIALS; PROBLEM SOLVING; TREES (MATHEMATICS);

DIRECTED ACYCLIC GRAPH (DAG); REFUTATIONS; SATISFIABILITY SOLVERS; SEARCH TREE;

LEARNING SYSTEMS;

EID: 33745465505     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11591191_40     Document Type: Conference Paper

References (25)

1. Alekhnovich, M., Johannsen, J., Pitassi, T., Urquhart, A.: An exponential separation between regular and unrestricted resolution. In: Proc. 34th ACM Symposium on Theory of Computing. (2002) 448-456
2. Anderson, R., Bledsoe, W.W.: A linear format for resolution with merging and a new technique for establishing completeness. Journal of the ACM 17 (1970) 525-534
3. Bayardo, Jr., R.J., Schrag, R.C.: Using CSP look-back techniques to solve realworld SAT instances. In: Proc. AAAI. (1997) 203-208
4. Beame, P., Kautz, H., Sabharwal, A.: Towards understanding and harnessing the potential of clause learning. Journal of Artificial Intelligence Research 22 (2004) 319-351
5. Beame, P., Pitassi, T.: Simplified and improved resolution lower bounds. In: Proc. 28th ACM Symposium on Theory of Computing. (1996)
6. Ben-Sasson, E., Wigderson, A.: Short proofs are narrow -resolution made simple. JACM 48 (2001) 149-168
7. Bonet, M., Galesi, N.: A study of proof search algorithms for resolution and polynomial calculus. In: Proc. 40th Symposium on Foundations of Computer Science. (1999) 422-432
8. Bonet, M., Galesi, N.: Optimality of size-width tradeoffs for resolution. Computational Complexity 10 (2001) 261-276
9. Clegg, M., Edmonds, J., Impagliazzo, R.: Using the Groebner basis algorithm to find proofs of unsatisfiability. In: Proc. 28th ACM Symposium on Theory of Computing. (1996) 174-183
10. Davis, M., Logemann, G., Loveland, D.: A machine program for theorem-proving. Communications of the ACM 5 (1962) 394-397
11. Davis, M., Putnam, H.: A computing procedure for quantification theory. Journal of the Association for Computing Machinery 7 (1960) 201-215
12. Dechter, R., Rish, I.: Directional resolution: the davis-putnam procedure, revisited. In: Proc. 4th Int'l Conf. on Principles of Knowledge Representation and Reasoning (KR'94), Morgan Kaufmann, San Francisco (1994) 134-145
13. Goldberg, E., Novikov, Y.: Berkmin: a fast and robust sat-solver. In: Proc. Design, Automation and Test in Europe. (2002) 142-149
14. Johnson, D.S., Trick, M.A., eds.: Cliques, Coloring, and Satisfiability: Second DIMACS Implementation Challenge. Volume 26 of DIMACS Series in Discrete Mathematics and Theoretical Computer Science. American Mathematical Society (1996)
15. Krishnamurthy, B.: Short proofs for tricky formulas. Acta Informatica 22 (1985) 253-274
16. Lee, S.J., Plaisted, D.A.: Eliminating duplication with the hyper-linking strategy. Journal of Automated Reasoning 9 (1992) 25-42
17. Letz, R., Mayr, K., Goller, C.: Controlled integration of the cut rule into connection tableau calculi. Journal of Automated Reasoning 13 (1994) 297-337
18. Marques-Silva, J.P., Sakallah, K.A.: GRASP-a search algorithm for propositional satisfiability. IEEE Transactions on Computers 48 (1999) 506-521
19. Moskewicz, M., Madigan, C., Zhao, Y., Zhang, L., Malik, S.: Chaff: Engineering an efficient SAT solver. In: 39th Design Automation Conference. (2001)
20. Plaisted, D.A. (private communication) (1984)
21. Plaisted, D.A.: The search efficiency of theorem proving strategies. In: 12th International Conference on Automated Deduction, Springer-Verlag (1994) 57-71
22. Stälmarck, G.: Short resolution proofs for a sequence of tricky formulas. Acta Informatica 33 (1996) 277-280
23. Tseitin, G.S.: On the complexity of derivation in propositional calculus. In Slisenko, A.O., ed.: Seminars in Mathematics v. 8: Studies in Constructive Mathematics and Mathematical Logic, Part II. Steklov Math. Inst., Leningrad (1968) 115-125 (English trans., 1970, Plenum.).
24. Zhang, H., Stickel, M.E.: Implementing the davis-putnam method. Journal of Automated Reasoning 24 (2000) 277-296
25. Zhang, L., Madigan, C., Moskewicz, M., Malik, S.: Efficient conflict driven learning in a boolean satisfiability solver. In: ICCAD. (2001)