BISC: Lotfi A. Zadeh; Santa Clara Valley Chapter of the IEEE/CS April 2002

From: masoud nikravesh (
Date: Fri Apr 19 2002 - 04:40:31 MEST

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    Berkeley Initiative in Soft Computing (BISC)

    ===============Prof. Lotfi Zadeh 's Talk ==========

            Santa Clara Valley Chapter of the IEEE/CS April 2002 Seminar

    Title: What is Fuzzy Logic and What are its Applications?

    Place: Building 320, Room 105 on the Stanford University Campus.

    Time: Wednesday, April 17 at 7:30PM
         light refreshments served from 7:00 to 7:30.

          What is Fuzzy Logic and What are its

                                            Lotfi A. Zadeh


                        Fuzzy logic has been and to some extent still is an
    object of controversy.
                        Some are turned-off by its name. But, more
    importantly, fuzzy logic is
                        tolerant of imprecision and partial truth. It is
    this tolerance that is in conflict
                        with the deep-seated Cartesian tradition of aiming
    at truth which is bivalent,
                        with no shades of gray allowed.

                        There are many misconceptions about fuzzy logic. In
    large measure, the
                        misconceptions reflect the fact that the term "fuzzy
    logic" has two distinct
                        interpretations. More specifically, in a narrow
    sense, fuzzy logic is the logic
                        of approximate reasoning: But in a wider sense which
    is in dominant use
                        today fuzzy logic, denoted as FL, is coextensive
    with the theory of fuzzy
                        sets, and contains fuzzy logic in a narrow sense as
    one of its branches. In
                        fact, most applications of FL involve modes of
    analysis which are
                        computational rather than logical in nature. Fuzzy
    logic, FL, has four
                        principal facets. First, the logical facet, FLl,
    which is fuzzy logic in its narrow
                        sense. Second, the set-theoretic facet, FLs, which
    is concerned with classes
                        having unsharp boundaries, that is, with fuzzy sets.
    Third, the relational facet,
                        FLr, which is concerned with linguistic variables,
    fuzzy if-then rules and
                        fuzzy relations. It is this facet that underlies
    almost all applications of fuzzy
                        logic in control, decision analysis, industrial
    systems and consumer products.
                        And fourth, the epistemic facet, FLe, which is
    concerned with knowledge,
                        meaning and linguistics. One of the important
    branches of FLe is a
                        possibility theory.

                        A concept which has a position of centrality in FL
    is that of fuzzy granularity
                        or, simply, f-granularity. F-granularity reflects
    the bounded ability of human
                        sensory organs and, ultimately, the brain, to
    resolve detail and store
                        information. In particular, human perceptions are,
    for the most part,
                        f-granular in the sense that (a) the boundaries of
    perceived classes are fuzzy,
                        and (b) the perceived attributes are granulated,
    with a granule being a clump
                        of values drawn together by indistinguishability,
    similarity, proximity or
                        functionality. In this perspective, the colors red,
    blue, green, etc., may be
                        viewed as labels of granules of perception of color.

                        Precision carries a cost. This is the main reason
    why in most of its
                        applications, the machinery of fuzzy logic is
    employed to exploit the
                        tolerance for imprecision to achieve tractability,
    robustness, and low solution
                        cost. This is what underlies the remarkable human
    capability to perform a
                        wide variety of physical and mental tasks, e.g.,
    drive in city traffic, based
                        solely on perceptions, without any measurements and
    any computations. It
                        is this capability that motivated the development of
                        computational theory of perceptions (CTP). Existing
    theories and, in
                        particular, probability theory, do not have the
    capability to operate on
                        perception-based information.

                        The computational theory of perceptions is a branch
    of the
                        fuzzy-logic-based methodology of computing with
    words (CW).
                        Development of the methodology of computing with
    words is an important
                        event in the evolution of fuzzy logic. Eventually,
    it may lead to a radical
                        enlargement of the role of natural languages in
    information processing,
                        decision, and control.
                        In Building 320, Room 105 on the Stanford University
                        The Seminar will be on Wednesday, April 17 at 7:30
    in the evening with
                        light refreshments served from 7:00 to 7:30.
                         About the Speaker
                        Lofti Zadeh is an IEEE Fellow and 1995 IEEE Medal of
    Honor Recipient,
                        he is a Professor in the Graduate School and
    director of the Berkeley
                        Initiative in Soft Computing (BISC), Computer
    Science Division and the
                        Electronics Laboratory, Department of EECS,
    University of California,
                        Berkeley. Dr. Zadeh is the original creator of Fuzzy

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