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Different Classes of Graphs to Represent Microstructures for CSPs

机译:不同类别的图形代表CSP的微结构

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The CSP formalism has shown, for many years, its interest for the representation of numerous kinds of problems, and also often provide effective resolution methods in practice. This formalism has also provided a useful framework for the knowledge representation as well as to implement efficient methods for reasoning about knowledge. The data of a CSP are usually expressed in terms of a constraint network. This network is a (constraints) graph when the arity of the constraints is equal to two (binary constraints), or a (constraint) hypergraph in the case of constraints of arbitrary arity, which is generally the case for problems of real life. The study of the structural properties of these networks has made it possible to highlight certain properties, which led to the definition of new tractable classes, but in most cases, they have been defined for the restricted case of binary constraints. So, several representations by graphs have been proposed for the study of constraint hypergraphs to extend the known results to the binary case. Another approach, finer, is interested in the study of the microstructure of CSP, which is defined by graphs. This helped, offering a new theoretical framework to propose other tractable classes. In this paper, we propose to extend the notion of microstructure to any type of CSP. For this, we propose three kinds of graphs that can take into account the constraints of arbitrary arity. We show how these new theoretical tools can already provide a framework for developing new tractable classes for CSPs. We think that these new representations should be of interest for the community, firstly for the generalization of existing results, but also to obtain original results.
机译:多年来,CSP形式主义已经表明了其对代表各种问题的兴趣,并且在实践中通常还提供了有效的解决方法。这种形式主义还为知识表示提供了有用的框架,并为知识的推理提供了有效的方法。 CSP的数据通常用约束网络表示。当约束的奇数等于两个(二元约束)时,该网络是一个(约束)图,或者在任意Arity的约束情况下(通常是现实生活中的问题),该网络是(约束)超图。对这些网络的结构特性的研究使得可能突出显示某些特性,从而导致了新的易处理类的定义,但是在大多数情况下,它们是针对二元约束的受限情况而定义的。因此,提出了几种图形表示法来研究约束超图,以将已知结果扩展到二进制情况。更好的另一种方法是研究CSP的微观结构,该方法由图形定义。这有所帮助,为提出其他易处理的课程提供了新的理论框架。在本文中,我们建议将微观结构的概念扩展到任何类型的CSP。为此,我们提出了三种可以考虑任意Arity约束的图。我们将展示这些新的理论工具如何为开发CSP的新易处理类提供框架。我们认为这些新的表示形式应该引起社区的兴趣,首先是为了对现有结果进行概括,而且还要获得原始结果。

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    LSIS - UMR CNRS 7296 Aix-Marseille Universite Avenue Escadrille Normandie-Niemen 13397 Marseille Cedex 20, France;

    LSIS - UMR CNRS 7296 Aix-Marseille Universite Avenue Escadrille Normandie-Niemen 13397 Marseille Cedex 20, France;

    LSIS - UMR CNRS 7296 Aix-Marseille Universite Avenue Escadrille Normandie-Niemen 13397 Marseille Cedex 20, France;

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