Connectionist AI? Workshop at IJCAI-89. Call for participation

[Lokendra Shastri]

                        IJCAI-89 WORKSHOP  
                      CALL FOR PARTICIPATION  

                       CONNECTIONIST AI?


Motivation and Agenda

The focus of the workshop is to define critical issues that
comprise the problem of systematic rule governed processes
and connectionist architectures. The outcome of the workshop
is to elaborate what the problem is and to motivate cross-talk
between the connectionist and AI research communities.

Numerous claims and counter claims have been made about
the nature of connectionist models and how they relate to rule
governed behavior. We feel that some researchers tend to oversimplify
connectionism and underestimate what it has to offer. At the same time
some others make very strong claims about connectionism and tend to
underestimate the complexity of the AI problem and ignore insights
obtained over years of research in AI and cognitive science. 
We also feel that some underlying problems in the discussions have 
never been raised.

Through this workshop we hope to gain a better understanding of 
specific issues related to the integration of rules with
connectionist processing approaches and to be able to more clearly
specify critical problems that need to be addressed if a
reconciliation between the approaches is warranted.


Specific issues to be discussed


Introductory Discussions - (Session I)

  1.  There are a number of variations on connectionism such as 
      parallel distributed processing, localist or structured connectionist
      models, neural nets. What are the core aspects of connectionist models?

  2.  What is a rule? Aspects of rules to be addressed include -
      structure and representation of rules and control of rule-based
      processes.

Reconciling rules with connectionism -- the alternatives? (Session
II)

  1.  Is there a clash between rules and connectionist architectures?
      It is often asserted that connectionist models are "non-symbolic" or 
      "sub-symbolic", and hence, fundamentally different from traditional AI
       approaches. Examine this claim?





   2. Should connectionist architectures compute rules? If so, what kind of
      rules? If not, how does one reconcile the approach with rules as
      characteristics of performance? 

Can connectionism contribute to AI? (Session III)

   1. It is claimed that connectionism just provides an interesting
      implementation paradigm. What is meant by "an implementation 
      paradigm"?   Can an implementation paradigm offer crucial 
      insights into problems?

   2.  Evaluate the contributions made by recent work in Connectionism to  
       central problems in AI  such as representation, reasoning, and learning.

Format

Our aim is to gather around 25 experts from within mainstream AI
as well as connectionism to discuss the above issues in depth.
The workshop will consist of three 3-hour discussion sessions spread
over one and a half days There will not be any presentations but only
moderated discussions.


Participation

Participation in the workshop is by invitation only and is limited to 
25 persons. Anyone who has published on issues directly related to the
workshop may apply.
Please submit one two page abstract outlining your position on one or more
topics to be discussed and a list of your recent publications on any of 
these topics. The abstract should be in 12 point font (the size of this text)
and double spaced.  (References may extend beyond the two page limit.)

Send three copies of your submission by APRIL 17, 1989 to:

                            Lokendra Shastri
                      Computer and Information Science
                         University of Pennsylvania,
                          Philadelphia, PA 19104.

Organizers:

Helen Gigley                             Lokendra Shastri 
Army Audiology and Speech Center         Computer and Information Science Dept
Walter Reed Army Medical Center          University of Pennsylvania 
Washington, D.C. 20012                   Philadelphia, PA  l9l04  
hgigley at note.nsf.gov                     shastri at cis.upenn.edu 

Alan Prince 
Psychology Department 
Brandeis University  
Waltham, MA 02254 
prince at brandeis.bitnet