From: fayegh@cs.ubc.ca (David Fayegh)
Subject: Re: Fuzzy Logic
Organization: Computer Science, University of B.C., Vancouver, B.C., Canada
Date: Wed, 29 Jul 92 08:27:42 GMT

tarokh@server.uwindsor.ca (TAROKH VAHID             ) writes:
>Summary: More questions about Dr. Zadeh

>I take your word that Dr. zadeh is Iranian, but would you please 
>write to me why his name is Asker. Did he change his name? I checked
>our library again and I found some books listed in his name, such as
>linear system theory and ... Our library records says that his name
>is Asker. I will appreciate any more elaborations.


These are questions that can be best answered by Dr. A. ZAdeh himself ... 
A matter of transliteration/pronunciation perhaps? There are many different 
pronunciations/transliterations for names .... for ex., I have known people 
who pronounce and/or transliterate "Vahid" as "Veheed" ...
Originally I thought that Asker was being used as an alternate transliteration
for Asghar. Now I have doubts ;-)  Its more likely that its an alternate
translit'n/pronounc'n for Askar.

I wonder if Dr. A. ZAdeh reads this newsgroup? :-) 
If so, please delight us with your response. Those of us in need
of an IrAnian here-o (sp ;-)) would sure appreciate it :-)

>Regarding the originality of his work, despite the fact that my
>knowledge of mathematical logic is next to empty set, I know
>from an undergraduate logic course that multivalued logics has
>been considered long ago. 

I guess if one goes back far enough, `re-searching' existing works
and literature, etc, one can easily trace fuzzy logic to Aristotle ;-)

The traditional methods of formal analysis/
reasoning/processing etc. require crisp/deterministic/precise 
representation of domain knowledge (rules/facts/...). Fuzzy logic 
overcomes certain aspects of this problem by allowing the effective 
representation of knowledge often considered fuzzy/stochastic/vague.
This utilization has amazing implications in certain control applications.

Using whatever mode of reasoning (induction/deduction/etc), in 
binary/dual `logic', for example, a particular statement (represented in
some `formal' language) is to be shown to be either true or false and 
nothing in between.  The aim of a logic interpreter would be to 
determine the truth or falsity of a statement represented in our
most favorite dialect of logic. In what you call `multivalued' logic,
one would be interested in knowing whether a particular statement, is 
a member of a possibly infinite set  of values/tokens -- Again, nothing can be 
said about statements that are not in the set, or that, say, sometimes 
belong to the set and sometimes do not!, or, whose value lies somewhere 
in-between the existing elements of the set, etc.
Fuzzy arithmetic provides a convenient method for dealing with some
of the above problems.

Experience has shown that in most real-world problems, two major obstacles 
exist when attempting to adapt formal logic to model/represent/simulate
the underlying characteristics/behavior  of the `system' under 
design/investigation:

(1) real events/outcomes/situations are often very fuzzy/vague/stochastic
and not crisp/precise/deterministic and hence can not be adequately 
represented by the formalisms offered by binary/multivalued conventional
logics,

(2) even if we have apriori knowledge of events/outcomes/situations that
occur at precise points in time and space (absolute certainty, no vagueness),
the representation of the real-world system in its entirety would 
require much more detailed data than one could recognize/model/process etc.
using conventional formalisms of mathematical logic.

Fuzzy logic can help the designer who can "exploit tolerance for imprecision"

ZAdeh[Zadeh 1965, page 339] writes: "The notion of a fuzzy set provides
a convenient point of departure for the construction of a conceptual 
framework which parallels in many respects the framework used in the case
of ordinary sets, but is more general than the latter and, potentially, may
prove to have a much wider scope of applicability, particularly in the
fields of pattern classification and information processing. Essentially
such a framework provides a natural way of dealing with problems in which
the source of imprecision is the absence of sharply defined criteria of
class membership rather than the presence of random variables."
(Fuzzy Sets, appeared in: Information and Control 8 (1965) pages 338-353)

>                          Would anybody out there elaborate more
>about distinction of his works from those done before.

hmmm this would be a good topic for a term paper in a course
on fuzzy logic ... 

>I appreciate your respond.

Glad to respond

>                      Thank You 
>                      Vahid

Cheers for now,  --df