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CFP: Self-organization in Representations for EAs, GECCO WS on

Ivan Garibay igaribay at cs.ucf.edu
Wed Dec 17 16:30:31 EST 2003

[Apologies if you receive this more than once]

                 Workshop Announcement and Call for Papers

    Self-organization in Representations for Evolutionary Algorithms:
                    Building complexity from simplicity 

                       to be held as part of the
          Genetic and Evolutionary Computation Conference (GECCO)
                        Seattle, Washington USA
                 June 26-30, 2004 (Saturday - Wednesday)

Papers submission deadline: March 1, 2004 (email: igaribay at cs.ucf.edu)

The success of evolutionary algorithms in a wide range of otherwise 
intractable problems has promoted its use. As evolutionary algorithms 
are applied to increasingly difficult problems that require increasingly 
complex solutions, they face a number of problems: premature convergence 
to suboptimal solutions, stagnation of search in large search spaces, 
negative epistatic effects, disruption of large building blocks, among 
others. Natural evolution, on the other hand, seems to not have any 
problem evolving strikingly complex self-organized solutions. 
Self-organization is present in almost every level of natural 
evolution: gene regulation networks, proteins interaction networks, 
metabolic pathways, cellular organization, etc; but it is not usually 
present in evolutionary algorithms. Nature evolves instructions that 
produce organisms by a process of self-organization. Perhaps the 
self-organization of genotypic instructions into phenotypes is a key 
missing ingredient necessary for unleashing the evolution of complex 
and scalable solutions with emergent phenomena such as: scale-free-ness, 
adaptability, innovation, evolvability, and robustness. This workshop 
will focus on domain-independent methods for representing complex 
solutions with relatively simple self-organizable building blocks. 

Topics of interest include (not limited to)

* Models of complexity building using self-organization 
* Self-organized development: embryogenesis, growth 
* Emergent behavior in representations 
* Methods of fitness assignment for self-organized individuals 
  (the price of non-programmability) 
* Methods of design and evaluation of self-organizable building blocks 
* Scalability of self-organizational processes to high complexities 
* Self-organization theoretical approaches: complexity, chaos, synergetics, 
  self-organized criticality, non-equilibrium thermodynamics, etc. 
* Artificial self-organized systems 
* NFL: what can we trade to get complexity and scalability in solutions? 

Workshop Format

This workshop seeks to bring together researchers from diverse problem 
domains to informally discuss issues related to the representation of 
complex solutions using self-organization of simple building blocks 
for evolutionary algorithms in particular, and the issue of building 
complexity from simplicity in general. We plan to have a series of 
short technical presentations followed by a panel discussion. 
We welcome technical papers describing completed or on-going research 
as well as position papers outlining current research issues, 
approaches or research agendas. We also welcome suggestions to panel 
discussions. Preprints will be circulated by email prior to the meeting. 

Workshop Submission Instructions:

Please submit a 3-4 page outline of a proposed contribution via email 
to igaribay at cs.ucf.edu in PS or PDF format. 
Accepted papers will be published in the GECCO-2004 workshops

Important Dates

Papers Due: March 1, 2004
Acceptance notices: March 17, 2004
Early Registration (GECCO-2004): March 19, 2004
Camera Ready: April 16, 2004
Workshop: June 27, 2004

Attendance: Open to all GECCO 2004 attendees 

 Ivan I. Garibay, Greg Holifield and Dr. Annie S. Wu
 Evolutionary Computation Laboratory - University of Central Florida

For more information, comments or suggestions please email Ivan Garibay 
at igaribay at cs.ucf.edu or visit http://ivan.research.ucf.edu/SOEA.htm


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