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CFP: OBUPM-2001 Workshop at GECCO-2001



         3rd (and the last) Call for Participation

                       OBUPM-2001

             OPTIMIZATION BY BUILDING AND USING
                 PROBABILISTIC MODELS 2001

                 Bird-of-a-feather Workshop
                          at the 
     Genetic and Evolutionary Computation Conference 2001
                      ( GECCO-2001 )

 San Francisco, California, July 7 - 11, 2001 (Sat - Wed) 


IMPORTANT DATES

Paper submission deadline:             March 9, 2001
Decisions will be mailed by:           April 1, 2001
Submissions of camera-ready papers:    April 20, 2001
Presentation:                          July 7, 2001

WORKSHOP SUMMARY

Algorithms that replace two-parent recombination of genetic 
algorithms by building and simulating a probabilistic model 
of promising solutions have received much attention over 
the past years. The proposed methods resolve many problems 
of other evolutionary algorithms and are increasingly used 
to solve various problem of practical and theoretical importance. 
Theory was designed to understand the dynamics of the algorithms 
as well as their limits.

The purpose of this workshop is to 
- review and describe the basic principles of discussed methods, 
- present recent developments in the covered area of research, 
- discuss current problems and future directions of research 
  in this area, and 
- encourage communication among active researchers in the area 
  and other participants. 

For more detailed submission guidelines and recent updates, 
see the workshop pages at
http://www-illigal.ge.uiuc.edu/obupm2001/index.html

ATTENDANCE

Attendance to the workshop is open to all GECCO attendees.
 
Further information will be posted on the workshop web pages
(www-illigal.ge.uiuc.edu/obupm2001/index.html) as it becomes 
available.

We are looking forward to your participation at the second
workshop OBUPM-2001 which is a great opportunity to meet and 
discuss the covered topics for researchers in this area of 
research as well as the ones who would like to learn more 
about using probabilistic models for a more powerful 
recombination.