From: rsun@athos.cs.ua.edu (Ron Sun)
Subject: CFP: integrating neural and symbolic processes
Organization: Department of Computer Science, University of Alabama
Date: Tue, 29 Sep 1992 20:06:18 GMT


                          CALL FOR PAPERS
    ARCHITECTURES FOR INTEGRATING NEURAL AND SYMBOLIC PROCESSES
            A Special Issue of Connection Science: a journal
              of AI, cognitive science and neurocomputing


Although there has been a great deal of research in integrating neural and
symbolic processes, both from a cognitive and/or applications viewpoint, there
has been relatively little effort in comparing, categorizing and combining
these fairly isolated approaches, especially from a cognitive perspective.
This special issue is intended to address the cognitive architectural aspects
of this integration: the issue will bring together various architectural
approaches as well as focus on specific architectures that solve particular
problems, that exhibit cognitive plausibility, that yield new insights, and
that show potential for scaling up.

Papers are expected to address the following questions, but are not limited to
such questions:
    * What have we achieved so far by integrating neural and 
symbolic processes?
    * What are the relative advantages/disadvantages of each approach?
    * How cognitively plausible is each proposed approach?
    * Is there any commonality among various architectural approaches?
Should we try to synthesize existing approaches?  How do we synthesize these
approaches?  (Does there exist a generic and uniquely correct cognitive
architecture?)
    * What are the problems, difficulties and outstanding issues in
integrating neural and symbolic processes?
    * How do symbolic representation and connectionist learning schemes
interact in integrated systems?

The papers can be either theoretical or experimental in scope, and can comment
on the current state of affairs and address what advances are necessary so
that continued progress can be made.  However, prospective authors should
emphasize the principles involved along with an explanation of why the
particular model works or does not work, and what it is we can learn from the
model. For example, does the model predict some testable behavior which can
lead to new insights?

All papers will be rigorously refereed, and should conform to the
following rules, in addition to the usual requirements of the journal.

Authors must submit five (5) printed copies of their papers to either of the
addresses listed below by January 5, 1993.  Notification of receipt will be
electronically mailed to the first author (or designated author) soon after
receipt.  Notification of acceptance or rejection of submitted papers will be
mailed to the first author (or designated author) by March 31, 1993.  Final
verson of accepted papers will be due May, 28, 1993.
 
All 5 copies of a submitted paper must be clearly 
legible. Neither computer files nor fax submissions are 
acceptable.  Submissions must be printed on 8 1/2 in. x 11 in.
or A4 paper using 12 point type (10 characters per inch 
for typewriters).
 
Each copy of the paper must have a title page (separate from the body of the
paper) containing the title of the paper, the names and addresses of all
authors, including e-mail addresses, and a short (less than 200 word)
abstract.



Submissions should be delivered to one of the following addresses:
Dr. Lawrence Bookman                    Prof. Ron Sun
Sun Microsystems Laboratories           Department of Computer Science          Two Federal Street                      The University of Alabama               
Billerica MA 01821, USA                 Tuscaloosa, AL 35487, USA               
lbookman@east.sun.com                   rsun@athos.cs.ua.edu

Potential arthors are strongly encouraged to contact the editors
as early as possible regarding their plans for submission.


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             Review Criteria
[Significance:]
How important is the work reported?  Does it attack an 
important/difficult problem or a peripheral/simple one?  
Does the approach offered advance the state of the art?

[Originality:]
Has this or similar work been previously reported?  Are 
the problems and approaches new?  Is this a 
novel combination of familiar techniques?  Does the 
paper point out differences from related research?  Is it 
re-inventing the wheel using new terminology?   

[Quality:]
Is the paper technically sound?  Does it carefully 
evaluate the strengths and limitations of its 
contribution?  How are its claims backed up?

[Clarity:]
Is the paper clearly written?  Does it motivate the research? 
Does the paper properly situate
itself with respect to previous work?  Are the results described and
evaluated? Is the paper organized in a logical fashion?

Xref: sparky comp.ai:3759 comp.ai.neural-nets:3764 alt.consciousness:565 comp.ai.philosophy:6298 sci.psychology:4021