Forming Neural Networks Through Efficient and Adaptive Coevolution 论文
1997Evolutionary Computation引用 307
Neural dynamics and brain functionReinforcement Learning in RoboticsEmbodied and Extended Cognition
摘要
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.