“A frequent source of misunderstanding has to do with the interpretation of fuzzy logic. The problem is that the term fuzzy logic has two different meanings. More specifically, in a narrow sense, fuzzy logic, FLn, is a logical system which may be viewed as an extension and generalization of classical multivalued logics. But in a wider sense, fuzzy logic, FLw is almost synonymous with the theory of fuzzy sets.”

— Lotfi A. Zadeh

In this context, what is important to recognize is that: (a) FLw is much broader than FLn and subsumes FLn as one of its branches; (b) the agenda of FLn is very different from the agendas of classical multivalued logics; and (c) at this juncture, the term fuzzy logic is usually used in its wide rather than narrow sense, effectively equating fuzzy logic with FLw
Zadeh (1995) in Foreword of George J. Klir Fuzzy sets and fuzzy logic: theory and applications.
1990s

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Lotfi A. Zadeh 18

Electrical engineer and computer scientist 1921–2017

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“A frequent source of misunderstanding has to do with the interpretation of fuzzy logic. The problem is that the term fuzzy logic has two different meanings. More specifically, in a narrow sense, fuzzy logic, FLn, is a logical system which may be viewed as an extension and generalization of classical multivalued logics. But in a wider sense, fuzzy logic, FLw is almost synonymous with the theory of fuzzy sets. In this context, what is important to recognize is that: (a) FLw is much broader than FLn and subsumes FLn as one of its branches; (b) the agenda of FLn is very different from the agendas of classical multivalued logics; and (c) at this juncture, the term fuzzy logic is usually used in its wide rather than narrow sense, effectively equating fuzzy logic with FLw</sub”

Lotfi A. Zadeh (1921–2017) Electrical engineer and computer scientist

Zadeh (1995) in Foreword of George J. Klir Fuzzy sets and fuzzy logic: theory and applications.
1990s

“Does fuzzy logic tickle?”

Steven Wright (1955) American actor and author

“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 fake, etc…. 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.”

George Klir (1932–2016) American computer scientist

Lotfi Asker Zadeh, George Klir, Bo Yuan (1996) Fuzzy Sets, Fuzzy Logic, and Fuzzy Systems: Selected Papers. p. 238.

Lotfi A. Zadeh (1921–2017) Electrical engineer and computer scientist

Lotfi Asker Zadeh, George Jiri Klir, Bo Yuan (1996) Fuzzy Sets, Fuzzy Logic, and Fuzzy Systems: Selected Papers. p. 238
1990s

“[ Fuzzy logic is ] a logic whose distinguishing features are (i) fuzzy truth-values expressed in linguistic terms, e. g., true, very true, more or less true, or somewhat true, false, nor very true and not very false, etc2.; (2) imprecise truth tables; and (3) rules of inference whose validity is relative to a context rather than exact.”

Lotfi A. Zadeh (1921–2017) Electrical engineer and computer scientist

Zadeh (1975) "Fuzzy logic and approximate reasoning". Synthese 30: p. 407
1970s

“I can't say that anything has been "exciting". Rather, I would choose the word "interesting". Not too long ago, the Chinese University of Hong Kong conducted a survey to determine which consumer products were using Fuzzy Logic. The result was a thick report, some 150-200 pages long-washing machines, camcorders, microwave ovens, etc. What interested me wasn't the particular applications so much as the breadth of applications-so many products were incorporating Fuzzy Logic.”

Lotfi A. Zadeh (1921–2017) Electrical engineer and computer scientist

About "What kinds of applications have you been excited to see develop?"
1990s, Interview with Lotfi Zadeh, Creator of Fuzzy Logic (1994)

“A fuzzy set is a class of objects with a continuum of grades of membership. Such a set is characterized by a membership (characteristic) function which assigns to each object a grade of membership ranging between zero and one. The notions of inclusion, union, intersection, complement, relation, convexity, etc., are extended to such sets, and various properties of these notions in the context of fuzzy sets are established. In particular, a separation theorem for convex fuzzy sets is proved without requiring that the fuzzy sets be disjoint.”

Lotfi A. Zadeh (1921–2017) Electrical engineer and computer scientist

Source: 1960s, Fuzzy sets (1965), p. 338

“Let me say quite categorically that there is no such thing as a fuzzy concept… We do talk about fuzzy things but they are not scientific concepts. Some people in the past have discovered certain interesting things, formulated their findings in a non-fuzzy way, and therefore we have progressed in science.”

Rudolf E. Kálmán (1930–2016) Hungarian-born American electrical engineer

Kálmán (1972), cited in: Lotfi A. Zadeh (2004) Fuzzy Logic Systems, origin, concepts and trends http://wi-consortium.org/wicweb/pdf/Zadeh.pdf November 10, 2004

“There is, then, a logical priority about the arrangements, and logic has nothing to do with time.”

Anthony Stafford Beer (1926–2002) British theorist, consultant, and professor

Source: Management Science (1968), Chapter 3, Quantified Insight, p. 74.

“Logic and truth are two very different things, but they often look the same to the mind that’s performing the logic.”

Theodore Sturgeon book More Than Human

Source: More Than Human (1953), Chapter 2, p. 97

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