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Circumspect descent prevails in solving random constraint satisfaction problems
We study the performance of stochastic local search algorithms for random instances of the K-satisfiability (K-SAT) problem. We present a stochastic local search algorithm, ChainSAT, which moves in the energy landscape of a problem instance by never going upwards in energy. ChainSAT is a focused alg...
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| 主要な著者: | , , , , , , |
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| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
National Academy of Sciences
2008
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| 主題: | |
| オンライン･アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC2563103/ https://ncbi.nlm.nih.gov/pubmed/18832149 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1073/pnas.0712263105 |
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