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Adding similarity-based reasoning capabilities to a Horn fragment of possibilistic logic with fuzzy constants

机译:为具有模糊常数的可能性逻辑的Horn片段添加基于相似度的推理功能

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摘要

PLFC is a first-order possibilistic logic dealing with fuzzy constants and fuzzily restricted quantifiers. The refutation proof method in PLFC is mainly based on a generalized resolution rule which allows an implicit graded unification among fuzzy constants. However, unification for precise object constants is classical. In order to use PLFC for similarity-based reasoning, in this paper we extend a Horn-rule sublogic of PLFC with similarity-based unification of object constants. The Horn-rule sublogic of PLFC we consider deals only with disjunctive fuzzy constants and it is equipped with a simple and efficient version of PLFC proof method. At the semantic level, it is extended by equipping each sort with a fuzzy similarity relation, and at the syntactic level, by fuzzily "enlarging" each non-fuzzy object constant in the antecedent of a Horn-rule by means of a fuzzy similarity relation.
机译:PLFC是处理模糊常数和模糊限制量词的一阶可能逻辑。 PLFC中的反证明方法主要基于通用分解规则,该规则允许模糊常数之间的隐式分级统一。然而,精确的对象常数的统一是经典的。为了将PLFC用于基于相似性的推理,在本文中,我们将PLFC的Horn-rule子逻辑扩展为基于相似性的对象常量统一。我们认为PLFC的Horn-rule子逻辑仅处理析取模糊常数,并且配备了简单有效的PLFC证明方法。在语义级别,通过为每种类别配备模糊相似关系来扩展它,在语法级别上,通过模糊相似性关系模糊地“放大” Horn-rule规则中的每个非模糊对象常量,从而对其进行扩展。 。

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