David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Ezio Di Nucci
Jonathan Jenkins Ichikawa
Jack Alan Reynolds
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Synthese 30 (3-4):407-428 (1975)
The term fuzzy logic is used in this paper to describe an imprecise logical system, FL, in which the truth-values are fuzzy subsets of the unit interval with linguistic labels such as true, false, not true, very true, quite true, not very true and not very false, etc. The truth-value set, , of FL is assumed to be generated by a context-free grammar, with a semantic rule providing a means of computing the meaning of each linguistic truth-value in as a fuzzy subset of [0, 1].Since is not closed under the operations of negation, conjunction, disjunction and implication, the result of an operation on truth-values in requires, in general, a linguistic approximation by a truth-value in . As a consequence, the truth tables and the rules of inference in fuzzy logic are (i) inexact and (ii) dependent on the meaning associated with the primary truth-value true as well as the modifiers very, quite, more or less, etc.
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Citations of this work BETA
Sam Alxatib & Francis Jeffry Pelletier (2011). The Psychology of Vagueness: Borderline Cases and Contradictions. Mind and Language 26 (3):287-326.
Elia Zardini (2008). A Model of Tolerance. Studia Logica 90 (3):337-368.
Andreas Blume & Oliver Board (2013). Intentional Vagueness. Erkenntnis 79 (S4):1-45.
Joseph Y. Halpern (2008). Intransitivity and Vagueness. Review of Symbolic Logic 1 (4):530-547.
Bert Baumgaertner (2012). Vagueness Intuitions and the Mobility of Cognitive Sortals. Minds and Machines 22 (3):213-234.
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