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 me… - Lotfi A. Zadeh

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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, FL<sub>n</sub>, is a logical system which may be viewed as an extension and generalization of classical multivalued logics. But in a wider sense, fuzzy logic, FL<sub>w</sub> is almost synonymous with the theory of fuzzy sets. In this context, what is important to recognize is that: (a) FL<sub>w</sub> is much broader than FL<sub>n</sub> and subsumes FL<sub>n</sub> as one of its branches; (b) the agenda of FL<sub>n</sub> 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 FL<sub>w</sub>

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About Lotfi A. Zadeh

Lotfali Askar Zadeh (February 4, 1921 – September 6, 2017) was an Azerbaijani-born Iranian American mathematician, electrical engineer, computer scientist, artificial intelligence researcher, and professor emeritus of computer science at the University of California, Berkeley, known for the development of .

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Native Name: Lütfəli Rəhim oğlu Əsgərzadə
Alternative Names: Lotfi Zadeh Lotfi Asker Zadeh Lotfi Aliaskerzadeha Lotfali Askar-Zadeh Lotfali Askar Zadeh Lofti Zadeh Lofti A. Zadeh Lofti Askar Zadeh Lotfi A Zadeh Lofti A Zadeh Zadeh Lotfi Aliasker Zadeh Lütfi Zadə Lütfizadə Zadeh, Lotfi Asker Заде, Лотфи Заде Л. А. Заде Лютфи Аскер Заде, Лютфи Аскер Заде, Лютфи Заде, Лотфи А. Заде Лотфи Аскер Заде, Лотфи Аскер Заде Л. Заде Аскерзаде, Лютфали Аскер Заде, Лотфи Аскер Заде, Лютфи Лотфи Аскер Заде Лотфи А. Заде Лотфи Заде Л. Заде Лютфи Аскер Заде Лютфи А. Заде Лютфи Заде Л. А. Заде Лотфи Задех
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It was a biologist — Ludwig von Bertalanffy — who long ago perceived the essential unity of system concepts and techniques in the various fields of science and who in writings and lectures sought to attain recognition for “general systems theory” as a distinct scientific discipline. It is pertinent to note, however, that the work of Bertalannfy and his school, being motivated primarily by problems arising in the study of biological systems, is much more empirical and qualitative in spirit than the work of those system theorists who received their training in exact sciences. In fact, there is a fairly wide gap between what might be regarded as “animate” system theorists and “inanimate” system theorists at the present time, and it is not at all certain that this gap will be narrowed, much less closed, in the near future. There are some who feel this gap reflects the fundamental inadequacy of the conventional mathematics—the mathematics of precisely defined points, functions, sets, probability measures, etc.—for coping with the analysis of biological systems, and that to deal effectively with such systems, we need a radically different kind of mathematics, the mathematics of fuzzy or cloudy quantities which are not describable in terms of probability distributions. Indeed the need for such mathematics is becoming increasingly apparent even in the realms of inanimate systems

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[T]he successes of modern control theory in the design of highly accurate space navigation systems have stimulated its use in the theoretical analyses of economic and biological systems. Similarly, the effectiveness of computer simulation techniques in the macroscopic analyses of physical systems has brought into vogue the use of computer-based econometric models for purposes of forecasting, economic planning, arid management.

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