Subject: CFP: JETAI Special Issue on Learning in DAI Systems
From: [email-masked] (Gerhard Weiss)
Date: 31 Jan 1996 16:11:05 GMT
Newsgroups: comp.ai

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                       C A L L   F O R   P A P E R S                          

        ( http://www7.informatik.tu-muenchen.de/~weissg/si-jetai )

  JOURNAL OF EXPERIMENTAL AND THEORETICAL ARTIFICIAL INTELLIGENCE (JETAI)

                             Special Issue on

         LEARNING IN DISTRIBUTED ARTIFICIAL INTELLIGENCE SYSTEMS        

                       Guest Editor: Gerhard Weiss

      JETAI is an international journal published by Taylor & Francis
          ( http://turing.pacss.binghamton.edu/jetai/index.html );
  Editor-in-Chief: Eric Dietrich, State University of New York, Binghamton

Focus and Purpose
-----------------

Distributed Artificial Intelligence (DAI) is  concerned  with  the study and
design  of systems  composed  of  several  interacting  entities  which  are 
logically and often spatially distributed  and in some sense  can  be called 
intelligent.  The  two  principal  types of  DAI  systems that  are  usually 
distinguised  are  distributed  problem  solving  systems  and   multi-agent 
systems.  DAI systems  typically  are  very complex  and hard to specify  in 
their  dynamics and behavior.  It is therefore commonly  agreed  that  these
systems should be able to learn, that is, to self-improve their performance.

For this issue  high-quality papers are invited  that describe work  done at 
the intersection of Machine Learning and DAI.  The focus of this issue is on
all aspects of learning  in all kinds of DAI systems.  The purpose  of  this 
issue  is  to  draw  together  experimental, theoretical, and methodological
key  research  being  within  this   focus.  Relevant topics for  this issue 
include, but are not limited to, the following:

- concepts and models of learning in DAI systems
- requirements for and principles of learning in DAI systems
- applicability and limitations of traditional machine learning approaches
  in the context of DAI systems
- parallel and distributed (inductive, multistrategy, etc) learning in DAI 
  systems
- learning in DAI systems by knowledge acquisition/discovery/refinement,
  by advice taking, by negotiation, by observation, etc
- relationships between learning on the one hand and communication, 
  cooperation, coordination, etc on the other
- self-organization in DAI systems
- learning in robot teams
- adaptive distributed planning systems
- formal models of learning in DAI systems.

Papers describing  research on learning in DAI systems  carried out in other   
disciplines than AI are also particularly welcome.

Submission Information
----------------------

All prospective authors  should  contact  the  guest editor  (preferably via
E-mail)  prior to submission and  in any case  not later than April 7, 1996,
in order to  discuss  contribution ideas  and  suitablity  for  this  issue. 
Submissions should be send to  the guest editor.  For general information on
the submission format, consult the inside back cover of a recent JETAI issue 
or visit JETAI's home page at the URL address provided above.

Important Dates
---------------

April 7, 1996       contact guest editor
November 1, 1996    submission deadline
February 16, 1997   notification of acceptance
June 1, 1997        final manuscript + send to publisher
(issue 9/4          publication)

Contact Address
---------------

Dr. Gerhard Weiss
Institut fuer Informatik
Technische Universitaet Muenchen
D-80290 Muenchen, Germany

Email: [email-masked]
Tel:   +49 89 2105 2407
Fax:   +49 89 2105 8207
URL:   http://www7.informatik.tu-muenchen.de/~weissg

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