BISC Seminar, 1 February 1996, 4-5:00pm, 310 Soda

Michael Lee (
Mon, 29 Jan 1996 17:07:31 +0100


BISC Seminar lecture: February 1 1996, 4:00-5:00 pm
310 Soda Hall
University of California
Berkeley, CA 94720


The Role of Fuzzy Logic and Soft Computing in the
Conception, Design and Deployment of Intelligent Systems


Lotfi A. Zadeh
Computer Science Division
University of California
Berkeley, CA 94720


The past three years have witnessed a significant increase
in the rate of growth of MIQ (Machine Intelligence Quotient)
of consumer products and industrial systems. There are many
factors which account for the increase in question but the
most prominent among them is the rapidly growing use of soft
computing and especially fuzzy logic in the conception and
design of intelligent systems.

The principal aim of soft computing is to exploit the
tolerance for imprecision and uncertainty to achieve
tractability, robustness and low solution cost. At this
juncture, the principal constituents of soft computing (SC)
are fuzzy logic (FL), neurocomputing (NC) and probabilistic
reasoning (PR), with the latter subsuming genetic
algorithms, belief networks, chaotic systems and parts of
learning theory.

What is important about soft computing is that FL, NC and PR
are for the most part synergistic rather than competitive.
A concomitant of this synergism is the growing visibility of
systems in which FL, NC, and PR are used in combination. A
case in point is the rapidly growing number of neuro-fuzzy
consumer products and systems which employ a combination of
fuzzy logic and neu ral network techniques. We are also
beginning to see systems which are neuro-genetic, fuzzy-
genetic and neuro-fuzzy-genetic.

As one of the principal constituents of soft computing,
fuzzy logic is playing a key role in the con ception and
design of what might be called high MIQ systems. The
principal contribution of fuzzy logic is a methodology for
computing with words. By their nature, words are less
precise than numbers. In this perspective, the use of words
serves two main purposes: (a) as a way of dealing with
information which is not precise enough to justify the use
of numbers; and (b) exploiting the tolerance for imprecision
when precise information is available or can be obtained at
a cost.

Furthermore, the methodology of computing with words
provides a foundation for the develop ment of programming
languages which are much closer to natural languages than
the programming languages in current use.

Michael A. Lee
Post Doctoral Researcher
Berkeley Initiative in Soft Computing              Tel: +1-510-642-9827
Computer Science Division                          Fax: +1-510-642-5775
University of California                    Email:
Berkeley, CA 94720-1776 USA       WWW: