No subject

[Ron Sun]

Fuzzy logic (or fuzzy set theory in general) has widespread impact on
many different areas. It bears significant resemblances to connectionist 
models. Thus it is only natural to investigate systematically the 
similarity and difference between them, and how they can join force
towards a new kind of AI, especially I am interested in knowing if 
there are ways we can take things from fuzzy logic and apply them
in high level connectionist cognitive modeling. Anyway connectionist 
models must deal with the same problem: uncertainty and 
vagueness (fuzziness), which is what FL is for.
In terms of using evolutionary and learning algorithms (GA for example),
these numbers (degree of membership, etc) might be useful.

There are some work that I know of, e.g. Kosko's paper in J. of
Approx. Reasoning, and my own one (in Proc. IIth cogSci Conf. and
Proc IEA/AIE-89)

My questions are 
  1) Any other work in the area (the relation between the two;
     the combination of the two)? pointers? references?
  2) Any comments and opinions regarding the combination of coneectionism
     and fuzzy logic? 
  3) Any conferences, symposia or workshops dealing extensively with
     the issue (the combination of the two, not each individually)?


Ron Sun
Brandeis University
Computer Science
Waltham, MA 02254

  rsun%cs.brandeis.edu at relay.cs.net