Horn上界和重命名

Marina Langlois, R. Sloan, György Turán
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引用次数: 11

摘要

我们考虑计算CNF公式的可处理近似的问题,扩展Selman和Kautz的方法来计算Horn-LUB,以涉及变量的重命名。在这个扩展版本中,给出了近似质量的否定结果。另一方面,随机3-CNF的实验表明,新算法提高了运行时间和近似质量。输出大小和近似误差表现出“霍恩凹凸”现象:在某些中间密度范围内观察到单峰模式的最大值。我们也给出了对Horn公式产生伪随机满意赋值的实验结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Horn Upper Bounds and Renaming
We consider the problem of computing tractable approximations to CNF formulas, extending the approach of Selman and Kautz to compute the Horn-LUB to involve renaming of variables. Negative results are given for the quality of approximation in this extended version. On the other hand, experiments for random 3-CNF show that the new algorithms improve both running time and approximation quality. The output sizes and approximation errors exhibit a 'Horn bump' phenomenon: unimodal patterns are observed with maxima in some intermediate range of densities. We also present the results of experiments generating pseudo-random satisfying assignments for Horn formulas.
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