Parallel cooperative propositional theorem proving

Annals of Mathematics and Artificial Intelligence

Volumn 26, Issue 1-4, 1999, Pages 59-85

  Okushi, Fumiaki ^a,b  

^a Electronics for Imaging   (United States)

^b University of California Santa Cruz   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 0033269634     PISSN: 10122443     EISSN: None     Source Type: Journal    
DOI: 10.1023/a:1018946526109     Document Type: Article

References (27)

1. R.J. Bayardo, Jr. and R.C. Schrag, Using CSP look-back techniques to solve real-world SAT instances, in: Proceedings 14th National Conference on Artificial Intelligence (AAAI-97) (1997) pp. 203-208.
2. M. Böhm and E. Speckenmeyer, A fast parallel SAT-solver - Efficient workload balancing, Ann. Math. Artificial Intelligence 17(3-4) (1996) 381-400.
3. S.H. Clearwater, T. Hogg and B.A. Huberman, Cooperative problem solving, in: Computation: The Micro and the Macro View, ed. B.A. Huberman (World Scientific, 1992) pp. 33-70.
4. S.H. Clearwater, B.A. Huberman and T. Hogg, Cooperative solution of constraint satisfaction problems, Science 254(5035) (1991) 1181-1183.
5. M. Davis, G. Logemann and D. Loveland, A machine program for theorem-proving, Comm. of the ACM 5 (1962) 394-397.
6. M. Davis and H. Putnam, A computing procedure for quantification theory, Journal of the ACM 7 (1960) 201-215.
7. M.D. Ernst, T.D. Millstein and D.S. Weld, Automatic SAT-compilation of planning problems, in: 15th International Joint Conference on Artificial Intelligence (1997) pp. 1169-1176.
8. R.E. Fikes and N.J. Nilsson, STRIPS: A new approach to the application of theorem proving to problem solving, Artificial Intelligence 2(3/4) (1971) 189-208.
9. S. Fleisig, D.W. Loveland, A.K. Smiley and D.L. Yarmush, An implementation of the model elimination proof procedure, Journal of the ACM 21(1) (1974) 124-139.
10. C.P. Gomes, B. Selman and N. Crato, Heavy-tailed distributions in combinatorial search, in: Proceedings of the 3rd International Conference on Principles and Practice of Constraint Programming (CP97) (1997) pp. 121-135.
11. C. Green, Application of theorem proving to problem solving, in: Proceedings 1st International Joint Conference on Artificial Intelligence (1969).
12. T. Hogg and C.P. Williams, Solving the really hard problems with cooperative search, in: Proceedings 11th National Conference on Artificial Intelligence (AAAI-93) (1993) pp. 231-236.
13. H. Kautz and B. Selman, Planning as satisfiability, in: ECAI 92, 10th European Conference on Artificial Intelligence Proceedings (Wiley, Chichester, UK, 1992) pp. 359-363.
14. H. Kautz and B. Selman, Pushing the envelope: Planning, propositional logic, and stochastic search, in: Proceedings of the 13th National Conference on Artificial Intelligence (AAAI '96) (1996).
15. R. Letz, K. Mayr and C. Goller, Controlled integration of the cut rule into connection tableau calculi, J. Automated Reasoning 13(3) (1994) 297-337.
16. C.M. Li and Anbulagan, Heuristics based on unit propagation for satisfiability problem, in: Proceedings International Joint Conference on Artificial Intelligence (1997) pp. 366-371.
17. D.W. Loveland, A simplified format for the model elimination theorem-proving procedure, Journal of the ACM 16(3) (1969) 349-363.
18. W.G. Macready, A.G. Siapas and S.A. Kauffman, Criticality and parallelism in combinatorial optimization, Science 271 (1996).
19. J. Minker and G. Zanon, An extension to linear resolution with selection function, Inform. Process. Lett. 14(3) (1982) 191-194.
20. n steps, Discrete Appl. Math. 10 (1985) 287-295.
21. V.N. Rao and V. Kumar, On the efficiency of parallel backtracking, IEEE Trans. Parallel Distributed Systems 4(4) (1993) 427-437.
22. R. Shonkwiler and E. Van Vleck, Parallel speed-up of monte carlo methods for global optimization, J. Complexity 10 (1994) 64-95.
23. R.E. Shostak, Refutation graphs, Artificial Intelligence 7(1) (1976) 51-64.
24. E. Speckenmeyer, B. Monien and O. Vornberger, Superlinear speedup for parallel backtracking, in: Supercomputing. 1st International Conference Proceedings, eds. E.N. Houstis, T.S. Papatheodorou and C.D. Polychronopoulos (Springer, Berlin, 1988) pp. 985-993.
25. A. Van Gelder, Autarky pruning in propositional model elimination reduces failure redundancy, J. Automated Reasoning 23(2) (1999) 137-193.
26. A. Van Gelder and F. Okushi, A propositional theorem prover to solve planning and other problems, Ann. Math. Artificial Intelligence 26 (this issue) (1999) 87-112.
27. H. Zhang and M. Bonacina, Cumulating search in a distributed computing environment: A case study in parallel satisfiability, in: First International Symposium on Parallel Symbolic Computation PASCO '94, ed. H. Hong (World Scientific, 1994) pp. 422-431.