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» Incorporating Learning in Grid-Based Randomized SAT Solving
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AIMSA
2008
Springer
13 years 11 months ago
Incorporating Learning in Grid-Based Randomized SAT Solving
Abstract. Computational Grids provide a widely distributed computing environment suitable for randomized SAT solving. This paper develops techniques for incorporating learning, kno...
Antti Eero Johannes Hyvärinen, Tommi A. Juntt...
CP
2000
Springer
13 years 8 months ago
Using Randomization and Learning to Solve Hard Real-World Instances of Satisfiability
This paper addresses the interaction between randomization, with restart strategies, and learning, an often crucial technique for proving unsatisfiability. We use instances of SAT ...
Luís Baptista, João P. Marques Silva
IJCSA
2007
104views more  IJCSA 2007»
13 years 4 months ago
Solving the Satisfiability Problem Using Finite Learning Automata
A large number of problems that occur in knowledge-representation, learning, VLSI-design, and other areas of artificial intelligence, are essentially satisfiability problems. The ...
Ole-Christoffer Granmo, Noureddine Bouhmala
SAT
2005
Springer
133views Hardware» more  SAT 2005»
13 years 10 months ago
Solving Over-Constrained Problems with SAT Technology
Abstract. We present a new generic problem solving approach for overconstrained problems based on Max-SAT. We first define a clausal form formalism that deals with blocks of clau...
Josep Argelich, Felip Manyà
CP
2004
Springer
13 years 10 months ago
Understanding Random SAT: Beyond the Clauses-to-Variables Ratio
It is well known that the ratio of the number of clauses to the number of variables in a random k-SAT instance is highly correlated with the instance’s empirical hardness. We con...
Eugene Nudelman, Kevin Leyton-Brown, Holger H. Hoo...