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Extended possibilistic truth values
Author(s) -
de Tré Guy
Publication year - 2002
Publication title -
international journal of intelligent systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.291
H-Index - 87
eISSN - 1098-111X
pISSN - 0884-8173
DOI - 10.1002/int.10030
Subject(s) - truth value , computer science , artificial intelligence , mathematics , programming language
A problem with the modeling of uncertainty within the context of an information or knowledge‐based system is the handling of missing information. In this article, extended possibilistic truth values are introduced as a formal means to cope with this problem. The notion of an extended possibilistic truth value has been obtained from the assumption that the truth value of a proposition can be undefined. This is the case if the proposition cannot be evaluated due to the non‐applicability of (some of) its elements. By definition, an extended truth value can either be true, false, or undefined. Using these three values, a ternary strong Kleene propositional logic has been built. An uncertainty model for this logic is proposed, in order to model (linguistic) uncertainty concerning the extended truth value of a proposition. This uncertainty model is based on possibility measures, and leads to the concept of an extended possibilistic truth value. Finally, the algebraic properties of extended possibilistic truth values are presented. © 2002 Wiley Periodicals, Inc.