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Evolving artificial neural networks

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1 Author(s)
Xin Yao ; Sch. of Comput. Sci., Birmingham Univ., UK

Learning and evolution are two fundamental forms of adaptation. There has been a great interest in combining learning and evolution with artificial neural networks (ANNs) in recent years. This paper: 1) reviews different combinations between ANNs and evolutionary algorithms (EAs), including using EAs to evolve ANN connection weights, architectures, learning rules, and input features; 2) discusses different search operators which have been used in various EAs; and 3) points out possible future research directions. It is shown, through a considerably large literature review, that combinations between ANNs and EAs can lead to significantly better intelligent systems than relying on ANNs or EAs alone

Published in:

Proceedings of the IEEE  (Volume:87 ,  Issue: 9 )