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Fuzzy Set: 1965 … Fuzzy Logic: 1973 …
BISC: 1990 … Human-Machine Perception: 2000 - …
Achievements and principal contributionsLotfi Zadeh's first important work was his doctoral
dissertation on the frequency analysis of time-varying networks, which was
published in the Proceedings of the IRE in 1949. In this work, he introduced
the concept of a time-varying transfer function-a concept which in the
intervening years has found significant applications in the analysis of
linear time-varying systems and has gained him his first international
recognition. In 1950, in a joint paper with John R. Ragazzini
which appeared in the Journal of Applied Physics, he described an important
generalization of Wiener's theory of prediction. This work has found numerous
applications in the design of finite-memory filters and predictors and is
widely regarded as a classic in its field. In 1952, Lotfi Zadeh,
again in cooperation with John R. Ragazzini, has
pioneered in the development of the z-transform approach to the analysis of
sampled-data systems. This approach has become a standard method for the
analysis of such systems and is widely used in the design of control systems
and digital filters. In 1953, he developed a novel approach to the design
of nonlinear filters and constructed a hierarchy of nonlinear systems based
on the Volterra-Wiener representation. This
approach has provided a basis for the design of optimal nonlinear processors
for the detection of signals in noise. In 1963, Lotfi Zadeh
co-authored with Charles Desoer their classic text
on the state-space theory of linear systems. This book is widely regarded as
a landmark in the development of the state-space approach and its application
to control and systems analysis. The state-space approach is now the standard
tool in optimal control and is widely used in the analysis of a variety of
systems ranging from industrial robots to space guidance control. Prior to the publication of his seminal paper on
fuzzy sets in 1965, Lotfi Zadeh was recognized both
nationally and internationally as one of the leading contributors to the
development of system theory and its applications. His paper on fuzzy sets
marked the beginning of a new direction; by introducing the concept of a
fuzzy set, that is, a class with unsharp
boundaries, he provided a basis for a qualitative approach to the analysis of
complex systems in which linguistic rather than numerical variables are
employed to describe system behavior and performance. In this way, a much
better understanding of how to deal with uncertainty may be achieved, and
better models of human reasoning may be constructed. Although his unorthodox
ideas were initially met with some skepticism, they have gained wide
acceptance in recent years and have found numerous applications in fields
ranging from pattern analysis and system design to damage assessment and
industrial process control. Subsequent to the publication of his 1965 paper, Lotfi Zadeh has made a number of basic contributions to
the theory of fuzzy sets and its applications, particularly noteworthy of
which are the following: In the paper entitled, Probability Measures of Fuzzy
Events (1968), he introduced the concept of the probability measure of a
fuzzy event which later led to the concepts of cardinality and fuzzy
quantification. In a joint paper with R. E. Bellman entitled,
Decision-Making in a Fuzzy Environment (1970), he laid the foundation for
decision analysis in the presence of fuzzy goals and constraints. This work
formed the basis for a number of papers by other investigators on problems
relating to decision analysis under uncertainty. In a seminal paper entitled, Outline of a New
Approach to the Analysis of Complex Systems and Decision Processes (1973), be
introduced the concept of a linguistic variable and suggested its
applications to knowledge-based systems and intelligent control. This paper,
together with an earlier note entitled A Rationale for Fuzzy Control (1972),
laid a foundation for the technology of fuzzy logic control--a technology
which in the years ahead may have a wide-ranging impact on the design of
intelligent control systems. In a paper entitled, Fuzzy Sets as a Basis for a
Theory of Possibility (1978), he introduced the concept of possibility and
developed a theory which is likely to become an essential tool for dealing
with lexical imprecision and the management of uncertainty in knowledge-based
systems. In a paper entitled, PRUF-A Meaning-Representation Language for
Natural Languages (1978), he developed a novel system based on the theory of
possibility for representing the meaning of propositions in a natural
language. In a paper entitled, A Computational Approach to
Fuzzy Quantifiers in Natural Languages (1983), he developed a method for
dealing with fuzzy quantifiers which later led to a theory of commonsense
knowledge. In a paper entitled, The Role of Fuzzy Logic in the
Management of Uncertainty in Expert Systems (1983), he described a method of
applying fuzzy logic to the representation of imprecise information and
formulated a number of basic inference rules governing the combination of
evidence in expert systems. In a paper entitled, Syllogistic Reasoning in Fuzzy
Logic and its Application to Usuality and Reasoning
with Dispositions (1985), he developed a theory of fuzzy syllogistic
reasoning and introduced the basic concepts of usuality
and dispositionality. In a paper entitled, Outline of a Computational
Approach to Meaning and Knowledge Representation Based on a Concept of a
Generalized Assignment Statement (1986), he introduced the concept of a
generalized constraint -- a concept which subsequently played a key role in
the development of the computational theory of perceptions. In a paper entitled, Test-Score Semantics as a Basis
for a Computational Approach to the Representation of Meaning (1986), he
described a novel approach to the representation of meaning in natural
languages. A key idea in this approach involves the representation of the
meaning of a proposition as a constraint on a variable. In this way, the
problem of inference is reduced to the solution of a nonlinear program. In a paper entitled, A Computational Theory of
Dispositions (1987), he developed a theory of dispositions which provides a
realistic model for commonsense reasoning and is likely to become a widely
used tool for the management of uncertainty in knowledge-based systems and
the design of intelligent controllers for industrial use. In a paper entitled, Knowledge Representation in
Fuzzy Logic, (1989), he described a fuzzy- logic-based approach to the
representation of imprecise and commonsense knowledge. This work led to the
use of FA-Prolog as a meaning representation language for natural languages. In a paper entitled, Fuzzy Logic and the Calculus of
If-Then Rules (1991) and subsequent papers, he initiated the development of
the calculii of fuzzy rules, fuzzy graphs and fuzzy
probabilities. These calculii represent the
beginning of a new direction in fuzzy logic and its applications. In a paper entitiled,
Fuzzy Logic = Computing with Words (1996), he described a novel
interpretation of fuzzy logic which leads to the concept of compuing with words. In coming years, computing with
words is likely to evolve into an important methodology with wide- ranging
applications. In a paper entitled, Fuzzy Logic and the Calculi of Fuzzy Rules
and Fuzzy Graphs (1997), he described a general theory of fuzzy rules and
fuzzy graphs in the context of fuzzy logic, and related this theory to the
concept of fuzzy information granulation. In a paper entitled, Toward a Theory of Fuzzy
Information Granulation and its Centrality in Human Reasoning and Fuzzy Logic
(1997), he initiated a new approach to fuzzy logic which links fuzzy logic to
granular computing. The theory described in this paper is likely to have a
major impact on fuzzy logic and its applications. In a paper entitled, From Computing with Numbers to
Computing with Words -- From Manipulation of Measurements to Manipulation of
Perceptions (1999), he initiated a computational theory of perceptions based
on computing with words. This new theory may well become one of his most
important contributions, with wide-ranging applications in many fields of
science and engineering. Lotfi
Zadeh became Professor Emeritus in 1991 but remained active in teaching,
research and professional service. Among his major professional contributions
since his retirement has been the initiation of the Berkeley Initiative in
Soft Computing (BISC). BISC has over two thousand members and over one
hundred institutional affiliates. Currently, Lotfi
Zadeh is serving as a Professor in the The concept of soft computing -- which was
introduced by Lotfi Zadeh in 1991 -- serves to
highlight the emergence of computing methodologies in which the accent is on
exploiting the tolerance for imprecision and uncertainty to achieve
tractability, robustness and low solution cost. At this juncture, the
principal constituents of soft computing are fuzzy logic, neurocomputing,
evolutionary computing and probabilistic computing, with the later subsuming
belief networks, chaotic systems and parts of learning theory. What is
particularly important about soft computing is that it facilitates the use of
fuzzy logic, neurocomputing, evolutionary computing
and probabilistic computing in combination, leading to the concept of hybrid
intelligent systems. Such systems are rapidly growing in importance and
visibility. Currently, Lotfi Zadeh's work is focused on the development of the
methodology of computing with words and the computational theory of
perceptions. The computational theory of perceptions may be viewed as a new
direction in fuzzy logic. Optimized for Web browsers Version 5+. |
Short Curriculum Vitae
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Fuzzy Set: 1965 … Fuzzy Logic: 1973 … BISC: 1990 …
Human-Machine Perception: 2000 - … |
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