Minimality and convexity properties in spatial CSPs

Priti Chandra, A. K. Pujari
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引用次数: 7

Abstract

The research in qualitative reasoning and in spatial CSP is always investigated in the backdrop of its temporal counterpart - qualitative temporal reasoning and TCSP. Unlike the case of interval algebra (IA), the composition table of RCC, IA's so-called spatial counterpart, is in general neither complete nor extensional, the compositional consistency can be still a valid reasoning mechanism. Even in such a restricted situation, many of the known properties of IA have not been investigated for validity in the context of RCC. We address, in this paper two such properties-convexity and minimality. The importance of minimality cannot be underestimated as in a minimal network every label is feasible and hence determining all the consistent scenarios can be accomplished very efficiently. It is known that path consistency does not yield a minimal network for tractable classes of RCC-8. We represent RCC-8 relations as a partially ordered set and exploit the properties of partial ordering to derive very interesting theoretical results. We show here that there exists a convex class of relations of RCC-8 for which path consistency yields a minimal network. Our results are very important as it gives a sufficient condition for minimality and useful to generate all consistent scenarios whenever compositional consistency is a valid reasoning mechanism
空间csp的极小性和凸性
定性推理和空间CSP的研究一直是在定性时间推理和TCSP的时间对应物的背景下进行的。与区间代数(IA)不同,RCC的组合表,即IA的所谓空间对应物,通常既不完整也不扩展,组合一致性仍然可以是一个有效的推理机制。即使在如此有限的情况下,许多已知的IA特性也没有在RCC的背景下进行有效性研究。在本文中,我们讨论了两个这样的性质——凸性和极小性。最小化的重要性不容低估,因为在最小化网络中,每个标签都是可行的,因此确定所有一致的场景可以非常有效地完成。众所周知,对于RCC-8的可处理类,路径一致性不会产生最小网络。我们将RCC-8关系表示为偏序集,并利用偏序的性质推导出非常有趣的理论结果。我们在这里证明存在RCC-8的凸类关系,其路径一致性产生最小网络。我们的结果非常重要,因为它给出了最小化的充分条件,并且当组合一致性是一种有效的推理机制时,对于生成所有一致的场景非常有用
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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