This article is about the scientific theory of that name. For other uses, see Fuzzy logic (disambiguation).
Fuzzy logic is a form of many-valued logic in which the truth value of variables may be any real number between 0 and 1. It is employed to handle the concept of partial truth, where the truth value may range between completely true and completely false.[1] By contrast, in Boolean logic, the truth values of variables may only be the integer values 0 or 1.
The term fuzzy logic was introduced with the 1965 proposal of fuzzy set theory by mathematician Lotfi Zadeh.[2][3] Fuzzy logic had, however, been studied since the 1920s, as infinite-valued logic—notably by Łukasiewicz and Tarski.[4]
Fuzzy logic is based on the observation that people make decisions based on imprecise and non-numerical information. Fuzzy models or fuzzy sets are mathematical means of representing vagueness and imprecise information (hence the term fuzzy). These models have the capability of recognising, representing, manipulating, interpreting, and using data and information that are vague and lack certainty.[5][6]
Fuzzy logic has been applied to many fields, from control theory to artificial intelligence.
^Novák, V.; Perfilieva, I.; Močkoř, J. (1999). Mathematical principles of fuzzy logic. Dordrecht: Kluwer Academic. ISBN 978-0-7923-8595-0.
^"Fuzzy Logic". Stanford Encyclopedia of Philosophy. Bryant University. 23 July 2006. Retrieved 30 September 2008.
^Zadeh, L. A. (June 1965). "Fuzzy sets". Information and Control. 8 (3). San Diego: 338–353. doi:10.1016/S0019-9958(65)90241-X. ISSN 0019-9958. Zbl 0139.24606. Wikidata Q25938993.
^Pelletier, Francis Jeffry (2000). "Review of Metamathematics of fuzzy logics" (PDF). The Bulletin of Symbolic Logic. 6 (3): 342–346. doi:10.2307/421060. JSTOR 421060. Archived (PDF) from the original on 3 March 2016.
^"What is Fuzzy Logic? "Mechanical Engineering Discussion Forum"". mechanicalsite.com. Archived from the original on 11 November 2018. Retrieved 11 November 2018.
^Babuška, Robert (1998). Fuzzy Modeling for Control. Springer Science & Business Media. ISBN 978-94-011-4868-9.
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