Forming Neural Networks Through Efficient and Adaptive Coevolution

被引:178
作者
Moriarty, David E. [1 ]
Miikkulainen, Risto [2 ]
机构
[1] Univ So Calif, Inst Informat Sci, Marina Del Rey, CA 90292 USA
[2] Univ Texas Austin, Dept Comp Sci, Austin, TX 78712 USA
关键词
Symbiotic adaptive neuroevolution; coevolution; neural networks; diversity;
D O I
10.1162/evco.1997.5.4.373
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
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.
引用
收藏
页码:373 / 399
页数:27
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