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Abduction via C-tableaux and δ-resolution

机译:通过C-tableaux和δ分辨率诱拐

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摘要

The formalization of abductive reasoning has received increasing attention from logicians. However, few work is found beyond abduction in propositional logic, given that in a first order formalism, the undecidability problem naturally appears, and therefore an abductive problem cannot even be appropriately formulated. Still, many applications in artificial intelligence allow finite domains to work with, and this gives an opportunity to apply abduction in first order logic with restricted domains. In this paper, we present an approach to abductive reasoning in C-structures, first order structures with a finite domain in which each of its elements has a corresponding constant representing its interpretation. By using semantic tableaux with bounded depth, that is, C-tableaux (a modification of N-tableaux, introduced by the authors in previous papers) and δ-resolution calculus, we build an effective procedure for the searching of minimal abductive solutions within the proposed semantics.
机译:归纳推理的形式化已引起逻辑学家越来越多的关注。但是,在命题逻辑中,除了绑架外,几乎没有发现任何工作,因为在一阶形式主义中自然会出现不确定性问题,因此甚至不能适当地提出一个绑架问题。尽管如此,人工智能中的许多应用程序仍允许使用有限域,这提供了将绑架应用于具有受限域的一阶逻辑的机会。在本文中,我们提出了一种在C结构中进行归纳推理的方法,C结构是具有有限域的一阶结构,其中每个元素的每个元素都有一个代表其解释的常数。通过使用具有深度限制的语义表,即C-tableaux(对N-tableaux的修改,由作者在先前的论文中介绍)和δ分辨率演算,我们建立了一个有效的程序,用于搜索内部的最小绑架解。建议的语义。

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