Reasoning in inconsistent stratified knowledge bases

S. Benferhat, D. Dubois, H. Prade
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引用次数: 25

Abstract

This paper proposes a discussion of inconsistency-tolerant consequence relations in prioritized knowledge bases. These inference techniques extend methods for reasoning from inconsistent, non-stratified, knowledge bases to the case where priorities between formulas are available. Priorities between formulas are handled in the framework of possibility theory and allow for the use of pieces of information having various levels of confidence. A comparative analysis of several approaches is carried out, namely, the possibilistic inference and its extensions, three inference methods based on a selection of maximal consistent subsets of formulas, and two inference methods based on arguments.
在不一致的分层知识库中的推理
本文提出了优先知识库中容错推理关系的讨论。这些推理技术将推理方法从不一致的、非分层的知识库扩展到公式之间的优先级可用的情况。在可能性理论的框架内处理公式之间的优先级,并允许使用具有不同置信度的信息片段。对几种方法进行了比较分析,即可能性推理及其扩展、基于选择公式的极大一致子集的三种推理方法和基于参数的两种推理方法。
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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