AILOAug 29, 2016

Fuzzy Logic in Narrow Sense with Hedges

arXiv:1608.08033v12 citations
AI Analysis

This work addresses the problem of representing human knowledge under vagueness for researchers in fuzzy logic, but it appears incremental as it builds on existing graded syntax frameworks.

The paper tackles the limitation of classical logic in handling vagueness and uncertainty by extending fuzzy logic with graded syntax to incorporate linguistic hedges, resulting in logics that achieve Pavelka-style completeness.

Classical logic has a serious limitation in that it cannot cope with the issues of vagueness and uncertainty into which fall most modes of human reasoning. In order to provide a foundation for human knowledge representation and reasoning in the presence of vagueness, imprecision, and uncertainty, fuzzy logic should have the ability to deal with linguistic hedges, which play a very important role in the modification of fuzzy predicates. In this paper, we extend fuzzy logic in narrow sense with graded syntax, introduced by Novak et al., with many hedge connectives. In one case, each hedge does not have any dual one. In the other case, each hedge can have its own dual one. The resulting logics are shown to also have the Pavelka-style completeness

Foundations

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