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Plenary Lectures
Thursday, July 26, 2001
Evolution of Fuzzy Logic - From Past to Future
Lotfi A. Zadeh
University of California at Berkeley
USA
Abstract:
Fuzzy logic, FL, as we know it today, is much more than a logical system. Basically, FL has four principal facets: the logical facet, FL/L; the set-theoretic facet, FL/S; the relational facet, FL/R; and the epistemic facet, FL/E. The logical facet, FL/L, is fuzzy logic in its narrow sense, with the understanding that FL as a whole is fuzzy logic in its broad sense.
The set-theoretic facet, FL/S, has its roots in fuzzy set theory. The logical facet, FL/L, is rooted in multiple-valued logic, but has a very different agenda. The relational facet, FL/R, is the basis for most of the practical applications of fuzzy logic. And the epistemic facet, FL/E, relates to knowledge, language and meaning.
From a personal perspective, an important milestone in the evolution of fuzzy logic was the introduction of the concept of a linguistic variable and the concomitant concept of a fuzzy if-then rule. In one form or another, almost all applications of fuzzy logic employ these concepts. Another important milestone was the development of possibility theory and its penetration into many fields in which concept formation, recognition and reasoning play important roles.
During the eighties and into the nineties, we have witnessed a substantive migration of fuzzy logic-- and especially its set-theoretic facet-- into a wide range of fields in pure and applied mathematics, among them topology, algebra, logic, measure theory, and functional analysis. It should be noted that at this juncture, the Mathematical Sciences Net database lists over l0,000 papers in the mathematical literature which contain the word "fuzzy" in title.
In the eightees and early nineties, a preponderance of applications of fuzzy logic--and especially its relational facet--related to control. Fuzzy control remains a major application area, but the emergence of many other areas such as resource allocation, decision support, recognition, databases,biomedicine and finance, has reduced its dominance of applications. Thus, fuzzy control is likely to grow in visibility, importnce and acceptance within the field of control, but lose its position of centrality in fuzzy logic applications.
As one of the principal members of soft computing, fuzzy logic is increasingly used in combination with neurocomputing, evolutionary computing, probabilistic computing, chaotic computing and machine learning methodologies.This is a trend that is likely to grow in visibility and importance in the years ahead.
When I look into my crystal ball, I see a growing impact of fuzzy logic within the basic sciences, among them mathematics, physics, chemistry and, to a lesser extent, biology. In the long run, fuzzy logic may replace Aristotelian logic as a major component of the foundations of basic and applied sciences. This is likely to happen because the real world is much too complex to fit the Procrustean bed of bivalent logic and the underlying principle of the excluded middle.
In my view, the fuzzy-logic-based methodology of computing with words is likely to play a pivotal role in the transition from Aristotelean logic to fuzzy logic. As a methodology, computing with words lays the groundwork for a radical enlargement of the role of natural languages in science and engineering, and especially in information processing, decision and control. What will be recognized, eventually, is that the richness of natural languages will have to be harnessed to make it possible to build machines with much higher MIQ (Machine IQ) than those we can build today. This is a paradigm shift that we are likely to witness in coming years.
About the Speaker:
Lotfi A. Zadeh is a Professor in the Graduate School, Computer Science Division, Department of EECS, University of California, Berkeley. In addition, he is serving as the Director of BISC (Berkeley Initiative in Soft Computing). He is an alumnus of the University of Teheran, MIT and Columbia University. He held visiting appointments at the Institute for Advanced Study, Princeton, NJ; MIT; IBM Research Laboratory, San Jose, CA; SRI International, Menlo Park, CA; and the Center for the Study of Language and Information, Stanford University. His earlier work was concerned in the main with systems analysis, decision analysis and information systems. His current research is focused on fuzzy logic, computing with words and soft computing, which is a coalition of fuzzy logic, neurocomputing, evolutionary computing, probabilistic computing and parts of machine learning. The guiding principle of soft computing is that, in general, better solutions can be obtained by employing the constituent methodologies of soft computing in combination rather than in stand-alone mode.
Dr. Zadeh is a Fellow of the IEEE, AAAS, ACM and AAAI. He is a member of the National Academy of Engineering and a Foreign Member of the Russian Academy of Natural Sciences. He is a recipient of the IEEE Education Medal, the IEEE Richard W. Hamming Medal, the IEEE Medal of Honor, the ASME Rufus Oldenburger Medal, the B. Bolzano Medal of the Czech Academy of Sciences, the Kampe de Feriet Medal, the AACC Richard E. Bellman Central Heritage Award, the Grigore Moisil Prize, the Honda Prize, the Okawa Prize, the AIM Information Science Award, the IEEE-SMC J. P. Wohl Career Achievement Award, the SOFT Scientific Contribution Memorial Award of the Japan Society for Fuzzy Theory, and other awards and honorary doctorates. He has published extensively on a wide variety of subjects relating to the conception, design and analysis of information/intelligent systems, and is serving on the editorial boards of over fifty journals.
Friday, July 27, 2001
Language-Based Computing Environment
for Internet Communication between Brain and Society
Michio Sugeno
Brain Science Institute, RIKEN
Japan
Abstract:
It is said that the brain has evolved in connection with language. We first survey human intelligence that is characterized by the use of language. Language has two features. It is social semiotic, and it is also concerned with higher order functions of the brain. This fact enables language to play a role of interfacing the brain with society.
In order to develop human language technology, we suggest to apply systemic functional linguistics initiated by Halliday. We discuss a novel type of computing called "Everyday Language Computing" based on the idea of performing all information processing on computers using everyday language as a meta-language. In this context we are aiming at a paradigm shift from conventional number-based computing to language-based computing.
With this computing environment, people could communicate using the Internet with other humans, agents, computer resources and other social resources with everyday language just as they think and act, and without any particular knowledge of computers.
About the Speaker:
Michio Sugeno received his doctorate from the Department of Physics, University of Tokyo and served as Research Associate, Associate Professor and Full Professor at the Department of Control Engineering and Department of Systems Science, Tokyo Institute of Technology. Since 2000 he is Head of the Laboratory for Language-Based Intelligent Systems, Brain Science Institute, RIKEN in Wako, Japan. Dr. Sugeno is the recipient of the Pioneer Award from the IEEE Neural Network Council in 2000.
Saturday, July 28, 2001
Fuzzy Systems Applications in Operations Research and Management Science
I. B. Turksen
Department of Industrial Engineering
University of Toronto
Canada
Abstract:
A historical review of fuzzy system applications reveal that OR, Operations Research, and MS, Management Science, applications was started early in the development of fuzzy systems, even before the advent of fuzzy control applications. The phenomenal success of fuzzy control, with Japanese applications to consumer product, was a surprise even to L.A. Zadeh. But the development of fuzzy systems applications continued in OR and MS in the shadow of fuzzy control. It is forecasted that the novel application of fuzzy systems will appear more strongly in OR and MS for managerial decision support and control in the areas of strategic and tactical planning, resource allocation, scheduling, inventory control, logistics,etc., under the headings of fuzzy mathematical programming, fuzzy quality control, fuzzy network analysis and control, fuzzy consumer preference analysis, client credit worthiness, financial portfolio analysis, etc. Examples of these will be presented within a historical perspective and further potential will be predicted.
About the Speaker:
I.B. Türksen received his Ph.D. degree in Systems Management and Operations Research in 1969, from the University of Pittsburgh, PA. He joined the Faculty of Applied Science and Engineering at the University of Toronto in 1970 and became Full Professor in 1983. Since 1987, he has been Director of the Information/Intelligent Systems Laboratory. During the 1991-1992 academic year, he was Visiting Research Professor of LIFE, Laboratory for International Fuzzy Engineering, Chair of Fuzzy Theory at Tokyo Institute of Technology. During 1993-1994 academic year, he was Visiting Research Professor at the University of South Florida and Bilkent University. Currently he is the President of IFSA. His current research interests are on the foundations of fuzzy sets and logics, in particular on Type 2 fuzzy knowledge representation and reasoning, fuzzy truth tables and fuzzy normal forms, and on applications of intelligent manufacturing and process system models, as well as, management decision support system models for analysis diagnosis, prediction and intelligent control.
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