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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 ...
Lotfi Aliasker Zadeh [5] (/ ˈ z ɑː d eɪ /; Azerbaijani: Lütfi Rəhim oğlu Ələsgərzadə; [6] Persian: لطفی علیعسکرزاده; [2] 4 February 1921 – 6 September 2017) [1] [3] was a mathematician, computer scientist, electrical engineer, artificial intelligence researcher, and professor [7] of computer science at the University of California, Berkeley.
Fuzzy mathematics is the branch of mathematics including fuzzy set theory and fuzzy logic that deals with partial inclusion of elements in a set on a spectrum, as opposed to simple binary "yes" or "no" (0 or 1) inclusion. It started in 1965 after the publication of Lotfi Asker Zadeh's seminal work Fuzzy sets. [1]
A fuzzy set is a pair (,) where is a set (often required to be non-empty) and : [,] a membership function. The reference set (sometimes denoted by or ) is called universe of discourse, and for each , the value () is called the grade of membership of in (,).
Fuzzy logic is an aspect of computing that handles approximate reasoning. Typically, binary logic allows computers to make decisions on true or false reasons (0s and 1s); however, introducing fuzzy logic allows systems to handle the unknowns between 0 and 1.
A fuzzy control system is a control system based on fuzzy logic—a mathematical system that analyzes analog input values in terms of logical variables that take on continuous values between 0 and 1, in contrast to classical or digital logic, which operates on discrete values of either 1 or 0 (true or false, respectively).
Lotfi A. Zadeh at U.C. Berkeley publishes his first paper introducing fuzzy logic, "Fuzzy Sets" (Information and Control 8: 338–353). J. Alan Robinson invented a mechanical proof procedure, the Resolution Method, which allowed programs to work efficiently with formal logic as a representation language.
Fuzzy logic, developed by Lofti Zadeh in the 60s, began to be more widely used in AI and robotics. Evolutionary computation and artificial neural networks also handle imprecise information, and are classified as "soft".