Noise Strategies for Improving Local Search


It has recently been shown that local search is sur prisingly good at nding satisfying assignments for certain computationally hard classes of CNF formu las The performance of basic local search methods can be further enhanced by introducing mechanisms for escaping from local minima in the search space We will compare three such mechanisms simulated annealing random noise and a strategy called mixed random walk We show that mixed random walk is the superior strategy We also present results demon strating the e ectiveness of local search with walk for solving circuit synthesis and circuit diagnosis prob lems Finally we demonstrate that mixed random walk improves upon the best known methods for solv ing MAX SAT problems

Extracted Key Phrases

Citations per Year

976 Citations

Semantic Scholar estimates that this publication has 976 citations based on the available data.

See our FAQ for additional information.

Cite this paper

@inproceedings{Selman1994NoiseSF, title={Noise Strategies for Improving Local Search}, author={Bart Selman and Henry A. Kautz and Bram Cohen}, booktitle={AAAI}, year={1994} }