二阶一致性
Second-Order Consistencies
摘要：
在本文中，我们提出了一个全面的研究二阶导数（即，识别不一致的值对）来满足约束满足。我们建立了一个完整的图片之间存在的四个基本的二阶一致性，即路径一致性（PC），3-一致性（3C），双一致性（DC）和2-单弧一致性（2SAC），以及它们的保守和强的变种。有趣的是，对偶一致性是一个原始的属性，可以通过使用广义弧一致性（GAC）的执行结果来建立，这使得它很容易获得，因为约束求解器通常在搜索过程中维护GAC。在二元约束网络中，DC等价于PC，但它对已有约束的约束约束，称为保守对偶一致性（Conservative Dual Consistency，CDC），严格强于传统的由路径一致性导出的保守对偶，即部分路径一致性（Partial Path Consistency，PPC）和保守路径一致性（Conservative Path Consistency，CPC）。在介绍了一个通用的算法，以执行强（C）DC，我们提出了一个实验的结果，在广泛的基准，证明利益（保守）的双重一致性。特别是，我们发现，强制执行（C）DC搜索前明显提高了性能的MAC（算法，保持GAC在搜索过程中）的几个二进制和非二进制结构的问题。
英文摘要：
In this paper, we propose a comprehensive study of second-order consistencies (i.e., consistencies identifying inconsistent pairs of values) for constraint satisfaction. We build a full picture of the relationships existing between four basic second-order consistencies, namely path consistency (PC), 3-consistency (3C), dual consistency (DC) and 2-singleton arc consistency (2SAC), as well as their conservative and strong variants. Interestingly, dual consistency is an original property that can be established by using the outcome of the enforcement of generalized arc consistency (GAC), which makes it rather easy to obtain since constraint solvers typically maintain GAC during search. On binary constraint networks, DC is equivalent to PC, but its restriction to existing constraints, called conservative dual consistency (CDC), is strictly stronger than traditional conservative consistencies derived from path consistency, namely partial path consistency (PPC) and conservative path consistency (CPC). After introducing a general algorithm to enforce strong (C)DC, we present the results of an experimentation over a wide range of benchmarks that demonstrate the interest of (conservative) dual consistency. In particular, we show that enforcing (C)DC before search clearly improves the performance of MAC (the algorithm that maintains GAC during search) on several binary and non-binary structured problems.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
