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Evolutionary Computation

Winter 1997, Vol. 5, No. 4, Pages 373-399
(doi: 10.1162/evco.1997.5.4.373)
© 1997 by the Massachusetts Institute of Technology
Forming Neural Networks Through Efficient and Adaptive Coevolution
Article PDF (1.83 MB)
Abstract

This article demonstrates the advantages of a cooperative, coevolutionary search in difficult control problems. The symbiotic adaptive neuroevolution (SANE) system coevolves a population of neurons that cooperate to form a functioning neural network. In this process, neurons assume different but overlapping roles, resulting in a robust encoding of control behavior. SANE is shown to be more efficient and more adaptive and to maintain higher levels of diversity than the more common network-based population approaches. Further empirical studies illustrate the emergent neuron specializations and the different roles the neurons assume in the population.