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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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