CFP: Scalable Robotic Applications of Neural Networks

[Patrick van der Smagt]

              REMINDER: CALL FOR PAPERS
              Scalable Robotic Applications of Neural Networks
	      http://www.robotic.dlr.de/Smagt/CFP/

              Special Issue of "Applied Intelligence"

              Submission deadline: January 15, 2000

In this special issue, we want to address the question of whether there are
real robotic problems that can be better solved using existing
neuro-computational principles than by using other standard engineering
techniques. Where sensory-motor systems cannot be explicitly modeled, the
brain's success leads us to expect that approaches based on adaptive neural
control will someday provide a technically sound alternative. However,
today's robotic engineers are appropriately skeptical regarding use of
neural network principles because of the apparent scarcity of published
research that demonstrates scalability of solutions to complex robotic
control tasks. For example, like many traditional approaches, many neural
network control strategies do not scale well from a two-degree-of-freedom
robot arm to a seven degree-of-freedom system.

For this special issue, papers are sought that:

  1. introduce or review biologically plausible models of sensory-motor
     control that truly integrate action and perception;
  2. newly apply such models to the control of realistic robots, especially
     manipulators;
  3. describe hybrid robot control methodologies that incorporate cerebellar
     or other neuro-computational models (e.g., vision);
  4. provide a case history that clearly defines, or illustrates overcoming
     of, barriers to successful competition by neural network models for
     robot control.

The scalability of applications of biological models can only be fully
assessed in the context of demonstrations that are representative of
real-world complexities. Therefore, results on real hardware will generally
be preferred. However, results on well-simulated complex problems will be
preferred to results with hardware (e.g., 2 DoF robot arms) that can already
be optimally controlled with conventional, non-neural techniques.
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Special Issue Editors

Patrick van der Smagt
Institute of Robotics and System Dynamics
DLR (German Aerospace Research Center) Oberpfaffenhofen, Germany
smagt at dlr.de
http://www.robotic.dlr.de/Smagt/

Daniel Bullock
Cognitive and Neural Systems Department
Boston University
danb at cns.bu.edu
http://cns-web.bu.edu/faculty.html#bullock

Editor in Chief

Moonis Ali
Department of Computer Science
Southwest Texas State University
ma04 at swt.edu
http://www.cs.swt.edu
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Submission

Deadline for submitting papers: Jan 15, 2000. The journal's instructions to
authors can be read here. For this special issue, for review all papers must
be submitted by the above date in Postscript or PDF format via email to
smagt at dlr.de. Hardcopy submissions will not be accepted.

To the extent that time permits, the editors will invite short external
commentaries (to be published in the same issue) on the accepted papers.
Submitters should inform the editors if they do *not* want their paper
treated in an invited commentary. Suggestions of expert reviewers and
commentators are welcome.
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About the journal

The objective of Applied Intelligence (IJAI) is to provide a medium for
exchanging applied research on intelligent systems and technological
achievements. IJAI is currently in its eighth year of publication. In order
to meet the demand, the publication frequency has been increased from four
to six issues per year effective 1998. IJAI is abstracted and/or indexed by
twenty indexing publications. See http://www.wkap.nl/journals/apin.



Wishing you all a Merry Christmas and a Happy New Year!


Patrick
-- 
Dr Patrick van der Smagt                phone +49 8153 281152, fax -34
DLR/Institute of Robotics and Mechatronics                smagt at dlr.de
P.O.Box 1116, 82230 Wessling, Germany     http://www.robotic.de/Smagt/