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Forming Neural Networks Through Efficient and Adaptive Coevolution

Evolutionary ComputationPublished 1 December 1997
David E. Moriarty, Risto Miikkulainen
Citations307
SJR quartileQ2
SJR score0.71
SNIP1.44

TL;DR

The symbiotic adaptive neuroevolution system coevolves a population of neurons that cooperate to form a functioning neural network to be more efficient and more adaptive and to maintain higher levels of diversity than the more common network-based population approaches.

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.

Keywords

Computer ScienceNeuroscience