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Reasoning under inconsistency: A forgetting-based approach

机译:不一致下的推理:基于遗忘的方法

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摘要

In this paper, a fairly general framework for reasoning from inconsistent propositional bases is defined. Variable forgetting is used as a basic operation for weakening pieces of information so as to restore consistency. The key notion is that of recoveries, which are sets of variables whose forgetting enables restoring consistency. Several criteria for defining preferred recoveries are proposed, depending on whether the focus is laid on the relative relevance of the atoms or the relative entrenchment of the pieces of information (or both). Our framework encompasses several previous approaches as specific cases, including reasoning from preferred consistent subsets, and some forms of information merging. Interestingly, the gain in flexibility and generality offered by our framework does not imply a complexity shift compared to these specific cases.
机译:在本文中,定义了一个用于从不一致的命题基础进行推理的相当通用的框架。变量遗忘用作削弱信息片段以恢复一致性的基本操作。关键概念是可恢复性,可恢复性是指变量集,其遗忘可以恢复一致性。根据是将重点放在原子的相对相关性上,还是在信息片段的相对牢固性上(或两者)上,提出了几种定义优选回收率的标准。我们的框架涵盖了几种先前的作为特定案例的方法,包括从首选一致子集进行推理以及某些形式的信息合并。有趣的是,与这些特定情况相比,我们框架提供的灵活性和通用性并不意味着复杂性的改变。

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