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The Complexity of Minimal Inference Problem for Conservative Constraint Languages

机译:保守限制语言最小推理问题的复杂性

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We study the complexity of the inference problem for propositional circumscription (the minimal inference problem) over arbitrary finite domains. The problem is of fundamental importance in nonmonotonic logics and commonsense reasoning. The complexity of the problem for the two-element domain has been completely classified [Durand, Hermann, and Nordh, Trichotomy in the complexity of minimal inference, LICS 2009]. In this paper, we classify the complexity of the problem over all conservative languages. We consider a version of the problem parameterized by a set of relations (a constraint language), from which we are allowed to build a knowledge base, and where a linear order used to compare models is a part of an input. We show that in this setting the problem is either Π_2~P-complete, coNP-complete, or in P. The classification is based on a coNP-hardness proof for a new class of languages, an analysis of languages that do not express any member of the class and a new general polynomial-time algorithm solving the minimal inference problem for a large class of languages.
机译:我们研究了任意有限域的命题界定(最小推理问题)推理问题的复杂性。问题在于非单调逻辑和勤义推理的基本重要性。两个元素域的问题的复杂性已经完全分类[Durand,Hermann和Nordh,在最小推理的复杂性中,LICS 2009]的三分道。在本文中,我们对所有保守语言的问题的复杂性分类。我们考虑由一组关系(约束语言)参数化的问题的版本,从中允许我们构建知识库,以及用于比较模型的线性顺序是输入的一部分。我们展示在这个设置中,问题是π_2〜p-complete,conp-complete或p.分类是基于新语言的CONP硬度证明,分析了不表达的语言类别的成员和新的一般多项式算法解决了大类语言的最小推理问题。

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