////////////////////////////////////////////////////////////////////////

                2nd Call for Papers & Participation:

              Evolutionary and Self-Organizing Sensors,
                 Actuators and Processing Hardware
                           (ESOSAPH)

                       Invited Session at

                            KES 2006

                 Tenth International Conference on
     Knowledge-Based Intelligent Information & Engineering Systems

                     9-11. October 2006, Bournemouth, UK

////////////////////////////////////////////////////////////////////////

                         Program Chairs

           Daniel Polani (University of Hertfordshire, UK)
               Mikhail Prokopenko (CSIRO, Australia)

Session website:    http://homepages.feis.herts.ac.uk/~comqdp1/kes_2006.html

_________________________________________________________________

Introduction

Recent technology has witnessed the advent of cheap ubiquitous
sensing, processing and actuating capabilities for isolated,
distributed or collective robotic systems. These appear in the form of
intelligent materials, nano-motors and -sensors,
Micro-Electro-Mechanical Systems (MEMS), grid processors,
Avogadro-scale digital circuits and similar structures. Established
conventional AI computation paradigms do not harness the full
potential of this new type of technological ability that includes
dynamic reconfiguration, addition or removal of sensors, actuators or
processing hardware. Classical AI paradigms are inadequate to deal
with the requirements of these scenarios which require flexible and
adaptive acquisition, manipulation and distribution of information as
opposed to sterile off-line AI software designs detached from concrete
usage scenarios.

One is confronted with the necessity to adapt sensoric properties
and/or configuration to a situation or task at hand, discovery of new
sensoric modalities,the use of newly added actuators in novel ways,
the necessity of reconfiguring computational hardware after being
damaged, and much more. What all these requirements have in common is
that, in general, there cannot be a full a priori appreciation of the
possible scenarios that can occur during the lifetime of the involved
hardware and software.

On the other hand, biological systems are capable to tackle such
problems on a regular basis. E.g. the recovery of functionality in
experiments where sensoric or neural tissues are transplanted to other
than the original locations show that biological systems have a
powerful potential to reconfigure their "hardware" and "software" to
suit the relevant situation. Biologically inspired approaches, e.g.
evolutionary and neural methods, as well as self-organization to
tackle these challenges, have been increasingly found to be fruitful.
Evolutionary sensorics, self-organizing controllers, neural strategies
have all provided new insights, methodologies, towards the achievement
of self- and externally modified sensomotoric loops.

Solving these problems has an enormous potential: it would allow the
construction of robust, cheap autonomous vehicles, sensor/actuator
networks consisting of a large number of autonomous sensor/actuator
units ('agents') that interact with each other to obtain the best
results. It would open the way to apply novel sensing/actuation
materials for the construction of agents because the self-organized
adaptation mechanisms would be able to deal with the novelty.
_________________________________________________________________

Call for Contributions

We solicit papers for poster or oral presentations (20 minute talk)
reporting working in this exciting area. Talks should address an
interdisciplinary audience, but may nevertheless deal with issues at
the cutting edge of research.
_________________________________________________________________

   Topics

Possible topics for the invited session are or involve (this is not an
exhaustive list and other relevant topics may be covered):

      * evolution or self-organization of physical sensors and actuators
        (artificial, bio-inspired, and biological)
      * abstract models for the evolution, self-organization and
        adaptation of sensors, actuators and processing, and for detection
        of emergent behaviour
      * evolution of controllers (including, but not limited to neural or
        cellular architectures)
      * self-monitoring and self-repair of damaged sensoric, computational
        and communication architectures
      * self-organization in sensomotoric loops
      * self-organized adaptive communication (e.g. mechanisms for the
        emergence of communication protocols)
      * evolution or self-organized modularity and hierarchies
      * identification of relevant information and features in sensoric
        input and of relevant behaviours and activities in actuatoric
        output

If you are unsure whether your topic is adequate for submission to the
session, please contact the program chairs.
_________________________________________________________________

Important Dates

Submission of papers:       4 March 2006
Notification of acceptance: 15 April 2006

_________________________________________________________________

Submission

The submission should be no longer than 8 pages in Springer
format. Please refer to the session website

   http://homepages.feis.herts.ac.uk/~comqdp1/kes_2006.html

for details.

_________________________________________________________________

Program Committee

Hussein Abbass      UNSW-ADFA, Australia
Andrew Adamatzky    UWE, UK
Peter Dauscher      University of Mainz, Germany
Attila Egri-Nagy    University of Hertfordshire, UK
Hod Lipson          Cornell University, USA
Chrystopher Nehaniv University of Hertfordshire, UK
David Payton        Hughes Research Labs, USA
Don Price           CSIRO, Australia
William Prosser     NASA LaRC, USA
Claude Sammut       UNSW, Australia
Susan Stepney       University of York, UK
Ivan Tanev          Doshisha University, Japan
Alexander Tarakanov Academy of Sciences, Russia
_________________________________________________________________