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

From: masoud nikravesh (nikraves@eecs.berkeley.edu)
Date: Fri Apr 19 2002 - 04:40:31 MEST

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Berkeley Initiative in Soft Computing (BISC)
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===============Prof. Lotfi Zadeh 's Talk ==========

Santa Clara Valley Chapter of the IEEE/CS April 2002 Seminar
Details: http://www.siliconvalleycs.org

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
Applications?

Abstract

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
fuzzy-logic-based
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,
enlargement of the role of natural languages in
information processing,
decision, and control.
Location
In Building 320, Room 105 on the Stanford University
Campus.
When?
The Seminar will be on Wednesday, April 17 at 7:30
in the evening with
light refreshments served from 7:00 to 7:30.
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
Logic.

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