A new method for solving hard satisfiability problems 论文

1992引用 1188
Constraint Satisfaction and OptimizationFormal Methods in VerificationBayesian Modeling and Causal Inference

详细信息

发表日期
1992-07-12
发表年份
1992

关键词

Constraint Satisfaction and OptimizationFormal Methods in VerificationBayesian Modeling and Causal Inference

摘要

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 approaches such as the Davis-Putnam procedure or resolution. We also show that GSAT can solve structured satisfiability problems quickly. In particular, we solve encodings of graph coloring problems, N-queens, and Boolean induction. General application strategies and limitations of the approach are also discussed. GSAT is best viewed as a model-finding procedure. Its good performance suggests that it may be advantageous to reformulate reasoning tasks that have traditionally been viewed as theorem-proving problems as model-finding tasks. Introduction The property of NP-hardness is traditionally taken to be the barrier separating tasks that can be solved computationally with realistic resources fro...