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Functional Treewidth: Bounding Complexity in the Presence of Functional Dependencies

机译:功能树木宽度:在功能依赖性存在下有限复杂性

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Many reasoning problems in logic and constraint satisfaction have been shown to be exponential only in the treewidth of their interaction graph: a graph which captures the structural interactions among variables in a problem. It has long been observed in both logic and constraint satisfaction, however, that problems may be easy even when their treewidth is quite high. To bridge some of the gap between theoretical bounds and actual runtime, we propose a complexity parameter, called functional treewidth, which refines treewidth by being sensitive to non-structural aspects of a problem: functional dependencies in particular. This measure dominates treewidth and can be used to bound the size of CNF compilations, which permit a variety of queries in polytime, including clausal implication, existential quantification, and model counting. We present empirical results which show how the new measure can predict the complexity of certain benchmarks, that would have been considered quite difficult based on treewidth alone.
机译:逻辑和约束满足中的许多推理问题仅在其交互图的树宽中显示是指数的:一个图形,其在问题中捕获变量之间的结构相互作用。然而,它已经在逻辑和约束满足中观察到,即使他的树木宽度相当高,也可能很容易。为了弥合理论界和实际运行时之间的一些差距,我们提出了一个复杂的参数,称为功能树Width,它通过对问题的非结构方面敏感而改进树木宽度:特定功能依赖性。这项措施将TreeWidth占主导地位,可用于绑定CNF编译的大小,这允许多项时间中的各种查询,包括子态意义,存在量化和模型计数。我们展示了实证结果,展示了新措施如何预测某些基准的复杂性,这将基于独自的树木被认为是非常困难的。

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