Abstract
A general model for the coevolution of cooperating species is presented. This model is instantiated and tested in the domain of function optimization, and compared with a traditional GA-based function optimizer. The results are encouraging in two respects. They suggest ways in which the performance of GA and other EA-based optimizers can be improved, and they suggest a new approach to evolving complex structures such as neural networks and rule sets.
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© 1994 Springer-Verlag Berlin Heidelberg
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Potter, M.A., De Jong, K.A. (1994). A cooperative coevolutionary approach to function optimization. In: Davidor, Y., Schwefel, HP., Männer, R. (eds) Parallel Problem Solving from Nature — PPSN III. PPSN 1994. Lecture Notes in Computer Science, vol 866. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-58484-6_269
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DOI: https://doi.org/10.1007/3-540-58484-6_269
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