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A Graph Based Synthesis Algorithm for Solving CSPs

机译:一种基于图的CSP综合算法

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摘要

Many AI tasks can be formalized as constraint satisfaction problems (CSPs), which involve finding values for variables subject to a set of constraints. While solving a CSP is an NP-complete task in general, it is believed that efficiency can be significantly improved by exploiting the characteristics of the problem. In this paper, we present a solution synthesis algorithm called ω-CDGT which is an existing algorithm named CDGT augmented with a constraint representative graph called ω-graph. We show that the worst-case complexity of the ω-CDGT algorithm is better than other related algorithms.
机译:许多AI任务可以形式化为约束满足问题(CSP),其中涉及查找受一组约束约束的变量的值。虽然解决CSP通常是NP完成的任务,但可以认为,通过利用问题的特征可以显着提高效率。在本文中,我们提出了一种称为ω-CDGT的解决方案综合算法,这是一种现有的名为CDGT的算法,并增加了称为ω-graph的约束表示图。我们表明,ω-CDGT算法的最坏情况复杂度要好于其他相关算法。

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