编译csp:(不确定性)多值决策图的复杂性图

J. Amilhastre, H. Fargier, Alexandre Niveau, C. Pralet
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引用次数: 22

摘要

约束满足问题(csp)为表示各种各样的问题提供了一个强大的框架。困难在于,与csp相关的大多数请求都是np困难的。由于这些请求必须在线处理,因此建议使用多值决策图(mdd)作为编译csp的一种方法。在本文中,我们以NNF编译图的精神,绘制了mdd的编译图,根据mdd的简洁性以及它们的播放时间转换和查询来分析mdd。确定性有序mdd是有序二元决策图到非布尔域的泛化:毫不奇怪,它们具有类似的功能。更有趣的是,我们的研究提出了对非确定性有序mdd的兴趣:当限制在布尔域时,该片段将OBDD和DNF作为适当的子集捕获,并且具有接近DNNF的性能。与经典的确定性mdd的比较表明,放宽确定性要求会增加简洁性,并允许在多时间(通常是析取的)中满足更多的转换。随机问题的实验证实了简洁性的提高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Compiling CSPs: A Complexity Map of (Non-Deterministic) Multivalued Decision Diagrams
Constraint Satisfaction Problems (CSPs) offer a powerful framework for representing a great variety of problems. The difficulty is that most of the requests associated with CSPs are NP-hard. As these requests must be addressed online, Multivalued Decision Diagrams (MDDs) have been proposed as a way to compile CSPs. In the present paper, we draw a compilation map of MDDs, in the spirit of the NNF compilation map, analyzing MDDs according to their succinctness and to their playtime transformations and queries. Deterministic ordered MDDs are a generalization of ordered binary decision diagrams to non-Boolean domains: unsurprisingly, they have similar capabilities. More interestingly, our study puts forward the interest of non-deterministic ordered MDDs: when restricted to Boolean domains, this fragment captures OBDD and DNF as proper subsets and has performances close to those of DNNF. The comparison to classical, deterministic MDDs shows that relaxing the determinism requirement leads to an increase in succinctness and allows more transformations to be satisfied in polytime (typically, the disjunctive ones). Experiments on random problems confirm the gain in succinctness.
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