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Abstract: GSAT is a randomized local search procedure for solving propositional satisfiability problems. GSAT can solve hard, randomly generated problems that are an order of magnitude larger than those that can be handled by more traditional approaches, such as the Davis-Putnam procedure. This paper presents the results of numerous experiments we have performed with GSAT, in order to improve our understanding of its capabilities and limitations. We first characterize the space traversed by GSAT. We will ... (Update)
Context of citations to this paper: More
.... Therefore, incomplete techniques become more attractive, especially with problems in planning which include thousands of variables [13]. The easiness hardness of solving SAT depends on a phenomena known as phase transition [3] Problems before the phase transition are...
...losses. Means for 100 problems and 250 deletion occasions per problem. Further experimental details in later sections. previous one [SK93]. This serves to get min conflicts out of local minima, and the augmented procedure is effective in finding global minima for ordinary...
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BibTeX entry: (Update)
B. Selman and H. A. Kautz, An empirical study of greedy local search for satisfiability testing, Proc. of the 11th National Conf. on Artificial Intelligence (Washington, DC), 1993, pp. 46--51. http://citeseer.ist.psu.edu/selman93empirical.html More
@inproceedings{ selman93empirical,
author = "Bart Selman and Henry A. Kautz",
title = "An Empirical Study of Greedy Local Search for Satisfiability Testing",
booktitle = "Proceedings of {theEleventhNational} Conference on Artificial Intelligence({AAAI}-93)",
address = "Washington DC",
year = "1993",
url = "citeseer.ist.psu.edu/selman93empirical.html" }
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663 Some Philosophical Problems From the Standpoint of Artificia.. (context) - McCarthy, Hayes - 1969
459 A Computing Procedure for Quantification Theory (context) - Davis, Putnam - 1960
416 A New Method for Solving Hard Satisfiability Problems - Selman, Levesque et al. - 1992
371 Optimization by Simulated Annealing: an Experimental Evaluat.. (context) - Johnson, Aragon et al. - 1991
329 Where the Really Hard Problems Are - Peter, Bob et al. - 1991
320 Hard and Easy Distributions of SAT Problems - Mitchell, Selman et al. - 1992
218 AMPL: A Modeling Language for Mathematical Programming (context) - Fourer, Gay et al. - 1993
210 Minimizing Conflicts: a Heuristic Repair Method for Constrai.. - Minton, Johnston et al. - 1992
146 Domain-Independent Extensions to GSAT: Solving Large Structu.. - Selman, Kautz - 1993
145 Planning as Satisfiability - Kautz, Selman - 1992
126 The Feynman Lectures on Physics (context) - Feynman, Leighton et al. - 1989
100 Genetic Algorithms and Simulated Annealing (context) - Davis - 1987
92 Cooling Schedules for Optimal Annealing (context) - Hajek - 1988
85 Towards an Understanding of Hill-ClimbingProcedures for SAT - Gent, Walsh - 1993
70 Efficient Local Search for Very Large-Scale Satisfiability P.. (context) - Gu - 1992
59 On Selecting a Satisfying Truth Assignment (context) - Papadimitriou - 1991
51 Report on a SAT Competition - Buro, Kleine - 1992
41 Experimental Results on the Cross-Over Point in Satisfiabili.. (context) - Crawford, Auton - 1993
41 Using Deep Structure to Locate Hard Problems - William, Hogg - 1992
32 Large Cliques Elude the Metropolis Process (context) - Jerrum - 1992
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11 Evidence for a Satisfiability Threshold for Random 3CNF Form.. (context) - Larrabee, Tsuji - 1993
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2 Personal communication (context) - AAAI-, appear et al. - 1992
1 and Dechter (context) - Pinkas - 1992
1 A Neural Network Approach to the 3-Satisfiability Problem (context) - Johnson - 1989
1 Combinatorial optimization (context) - STOC-, Steiglitz - 1982
1 Breakout Method for Escaping from Local Minima (context) - AAAI-, Jose et al. - 1993
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