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A New Method for Solving Hard Satisfiability Problems
 AAAI
, 1992
"... We introduce a greedy local search procedure called GSAT for solving propositional satisfiability problems. Our experiments show that this procedure can be used to solve hard, randomly generated problems that are an order of magnitude larger than those that can be handled by more traditional approac ..."
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Cited by 734 (21 self)
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We introduce a greedy local search procedure called GSAT for solving propositional satisfiability problems. Our experiments show that this procedure can be used to solve hard, randomly generated problems that are an order of magnitude larger than those that can be handled by more traditional
Generating Hard Satisfiability Problems
 Artificial Intelligence
, 1996
"... We report results from largescale experiments in satisfiability testing. As has been observed by others, testing the satisfiability of random formulas often appears surprisingly easy. Here we show that by using the right distribution of instances, and appropriate parameter values, it is possible ..."
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Cited by 109 (2 self)
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, it is possible to generate random formulas that are hard, that is, for which satisfiability testing is quite difficult. Our results provide a benchmark for the evaluation of satisfiabilitytesting procedures. In Artificial Intelligence, 81 (19996) 1729. 1 Introduction Many computational tasks of interest
Simulated Annealing for Hard Satisfiability Problems
 In, Workshop
, 1993
"... Satisfiability (SAT) refers to the task of finding a truth assignment that makes an arbitrary boolean expression true. This paper compares a simulated annealing algorithm (SASAT) with GSAT (Selman et al., 1992), a greedy algorithm for solving satisfiability problems. GSAT can solve problem instances ..."
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Cited by 45 (0 self)
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instances that are extremely difficult for traditional satisfiability algorithms. Results suggest that SASAT scales up better as the number of variables increases, solving at least as many hard SAT problems with less effort. The paper then presents an ablation study that helps to explain the relative
Finding Hard Satisfiability Problems Using Bacterial Conjugation
, 1996
"... The Satisfiability Problem is an important problem, both in Artificial Intelligence and Complexity Theory. Recently, there have been attempts to find efficient algorithms to solve this problem based on the Greedy Algorithm. In order to test these algorithms effectively, hard problems are required. T ..."
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Cited by 10 (0 self)
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The Satisfiability Problem is an important problem, both in Artificial Intelligence and Complexity Theory. Recently, there have been attempts to find efficient algorithms to solve this problem based on the Greedy Algorithm. In order to test these algorithms effectively, hard problems are required
A NN Algorithm for Hard Satisfiability Problems
 Naval Research Laboratory
, 1993
"... Satisfiability (SAT) refers to the task of finding... This paper compares GSAT with a novel NN approach on that class of hard problems. The results indicate that the NN approach (NNSAT) spends more time "thinking" about which assignment to try next, yet searches far fewer assignments befor ..."
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Cited by 2 (1 self)
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Satisfiability (SAT) refers to the task of finding... This paper compares GSAT with a novel NN approach on that class of hard problems. The results indicate that the NN approach (NNSAT) spends more time "thinking" about which assignment to try next, yet searches far fewer assignments
Solving “Hard” Satisfiability Problems Using GridSAT
"... We present an improved version of GridSAT, a distributed and complete satisfiability solver. The solver is used to solve a set of “hard ” and previously unsolved set of satisfiability problems. We enhance the GridSAT solver, which is based on the sequential solver Chaff, in two main ways. First the ..."
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We present an improved version of GridSAT, a distributed and complete satisfiability solver. The solver is used to solve a set of “hard ” and previously unsolved set of satisfiability problems. We enhance the GridSAT solver, which is based on the sequential solver Chaff, in two main ways. First
A Two Phase Algorithm for Solving a Class of Hard Satisfiability Problems
 Operations Research Letters
, 1998
"... The DIMACS suite of satisfiability (SAT) benchmarks contains a set of instances that are very hard for existing algorithms. These instances arise from learning the parity function on 32 bits. In this paper we develop a two phase algorithm that is capable of solving these instances. In the first ph ..."
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Cited by 29 (6 self)
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The DIMACS suite of satisfiability (SAT) benchmarks contains a set of instances that are very hard for existing algorithms. These instances arise from learning the parity function on 32 bits. In this paper we develop a two phase algorithm that is capable of solving these instances. In the first
Distributed Problem Solving Without Communication  An Examination Of Computationally Hard Satisfiability Problems
 International Journal of Pattern Recognition and Arti Intelligence
, 2002
"... this paper, we extend and modify the ERA approach proposed in Ref. 13 to solve Propositional Satisfiability Problems (SATs). The new ERA approach involves a multiagent system where each agent only senses its local environment and applies some selforganizing rules for governing its movements. The ..."
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Cited by 2 (1 self)
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this paper, we extend and modify the ERA approach proposed in Ref. 13 to solve Propositional Satisfiability Problems (SATs). The new ERA approach involves a multiagent system where each agent only senses its local environment and applies some selforganizing rules for governing its movements
GSAT: A new method for solving hard satisfiability problems
, 1992
"... We introduce a greedy local search procedure called GSAT for solving propositional satis ability problems. Our experiments show that this procedure can be used to solve hard, randomly generated problems that are an order of magnitude larger than those that can be handled by more traditional approach ..."
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Cited by 8 (1 self)
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We introduce a greedy local search procedure called GSAT for solving propositional satis ability problems. Our experiments show that this procedure can be used to solve hard, randomly generated problems that are an order of magnitude larger than those that can be handled by more traditional
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