论文标题

表征追逐变体中的界限

Characterizing Boundedness in Chase Variants

论文作者

Delivorias, Stathis, Leclère, Michel, Mugnier, Marie-Laure, Ulliana, Federico

论文摘要

存在规则是一阶逻辑的积极片段,它通过允许在规则头中存在量化的变量来概括无功能的喇叭规则。该语言家族最近在本体介导的查询答案的背景下引起了重大兴趣。向前链接,也称为追逐,是计算包括存在的规则和事实组成的通用知识基础模型的基本工具。已经定义了几个追逐变体,它们在处理冗余的方式上有所不同。如果一组生存规则可确保在追逐深度上存在绑定,而与任何事实无关。确定一组规则是否有限是所有追逐变体的不可决定的问题。然而,当计算通用模型时,知道一组规则对某些追逐变体有限,如果界限仍然未知甚至很大,则在实践中无济于事。因此,我们调查了k结合问题的可决定性,该问题询问对给定规则的追逐的深度是否受整数k的限制。我们确定了一个通用属性,当通过追逐变体满足时,它会导致K结合度的可决定性。然后,我们表明,主要追逐变体可以满足这一属性,即遗忘,半斑点(又名Skolem)和受限的追逐及其广度优先版本。本文正在考虑逻辑编程理论和实践中的出版。

Existential rules are a positive fragment of first-order logic that generalizes function-free Horn rules by allowing existentially quantified variables in rule heads. This family of languages has recently attracted significant interest in the context of ontology-mediated query answering. Forward chaining, also known as the chase, is a fundamental tool for computing universal models of knowledge bases, which consist of existential rules and facts. Several chase variants have been defined, which differ on the way they handle redundancies. A set of existential rules is bounded if it ensures the existence of a bound on the depth of the chase, independently from any set of facts. Deciding if a set of rules is bounded is an undecidable problem for all chase variants. Nevertheless, when computing universal models, knowing that a set of rules is bounded for some chase variant does not help much in practice if the bound remains unknown or even very large. Hence, we investigate the decidability of the k-boundedness problem, which asks whether the depth of the chase for a given set of rules is bounded by an integer k. We identify a general property which, when satisfied by a chase variant, leads to the decidability of k-boundedness. We then show that the main chase variants satisfy this property, namely the oblivious, semi-oblivious (aka Skolem), and restricted chase, as well as their breadth-first versions. This paper is under consideration for publication in Theory and Practice of Logic Programming.

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