布尔代数与可拓规则的模型计数

Youjun Xu, D. Ouyang, Yuxin Ye
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引用次数: 3

摘要

模型计数是人工智能中的一个重要问题,在信息科学的许多领域都有应用。可拓规则是一种对模型进行计数的方法。但在条款长度较短或条款数量较大的情况下就不适用了。通过对可拓规则的研究,发现可满足性问题可以用命中集算法求解。在计算子句集的命中集后,用可拓规则对模型进行计数。因此,本文提出了一种MCBE算法。利用布尔代数,MCBE可以很容易地计算子句集的命中集。然后给出了具有扩展规则的模型个数。测试结果表明,当子句长度较短且子句数量足够大时,该算法比CDP和CER算法效率更高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Model Counting with Boolean Algebra and Extension Rule
Model counting is an important problem in artificial intelligence and is applied in several areas of information science. Extension rule is a method which could be used to count models. But it’s not appropriate when clause length is short or clause number is huge. After studying extension rule, we found that the satisfiability problem could be solved by hitting set algorithms. And the models could be counted with extension rule after calculating hitting sets of a clause set. Therefore, we proposed an algorithm MCBE in this paper. With Boolean algebra, MCBE could easily calculate hitting sets of a clause set. Then, it gives the number of models with extension rule. The test results show that when clause length is short and clause number is big enough, the algorithm is more efficiency than the algorithm CDP and CER.
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