Call for Papers
Soft Computing Journal
Special Issue on
Approximation and Learning in Evolutionary Computation
(Submission deadline has been extended to October 14, 2002)
Scope
In many real-world applications, it is often necessary to construct approximate models or reduced models for fitness function. One essential difficulty in applying evolutionary algorithms to the optimization of complex systems is the high time complexity of each fitness evaluation. Besides, in some applications, no explicit mathematical functions are available for fitness evaluations. Further more, approximate fitness models have also been proved useful in dealing with noisy and multi-modal fitness functions. Meanwhile, domain knowledge leaned during evolutionary optimization has proved to be very helpful in improving the performance of evolutionary algorithms. This special issue aims to put together a set of high-quality original contributions that reflect the state-of-art and recent advances on approximation and learning in evolutionary computation. Topics may include but not limited to:
- Off-line and on-line learning for constructing approximate fitness functions
- Evolution control and model management in evolutionary computation
- Guidance of genetic operations using approximations
- Machine learning techniques for knowledge incorporation into evolution
- Comparison of different modeling methods, such as neural networks, response surface and least squares methods, and probabilistic models for evolutionary computation
- Comparison of different sampling techniques for on-line and off-line learning
Submission
Three hard copies of the manuscript should be received before September 30, 2002. Electronic submissions in Word Document, postscript or pdf format are encouraged. The manuscript should include the mailing address, the e-mail address and the fax number of the corresponding author. Please refer to the
Instruction for Authors for further details on the manuscript preparation. Send all submissions to Yaochu Jin.
Guest Editors
Yaochu Jin
Honda Research Institute Europe
Carl-Legien-Str. 30
63073 Offenbach/Main
GERMANY
Emails: yaochu.jin@honda-ri.de
yaochu.jin@de.hrdeu.com
Phone : 0049-69-89011735
Fax: 0049-69-89011749
Sushil J. Louis
Department of Computer Science
University of Nevada, Reno
Reno, NV 89557, U.S.A.
Email: sushil@cs.unr.edu
Khaled Rasheed
Department of Computer Science
University of Georgia
Athens, GA 30602-7404
U.S.A.
Email: khaled@cs.uga.edu