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APIN
1998

Evolutionary Learning of Modular Neural Networks with Genetic Programming

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Evolutionary Learning of Modular Neural Networks with Genetic Programming
Evolutionary design of neural networks has shown a great potential as a powerful optimization tool. However, most evolutionary neural networks have not taken advantage of the fact that they can evolve from modules. This paper presents a hybrid method of modular neural networks and genetic programming as a promising model for evolutionary learning. This paper describes the concepts and methodologies for the evolvable model of modular neural networks, which might not only develop new functionality spontaneously, but also grow and evolve its own structure autonomously. We show the potential of the method by applying an evolved modular network to a visual categorization task with handwritten digits. Sophisticated network architectures as well as functional subsystems emerge from an initial set of randomly-connected networks. Moreover, the evolved neural network has reproduced some of the characteristics of natural visual system, such as the organization of coarse and fine processing of st...
Sung-Bae Cho, Katsunori Shimohara
Added 21 Dec 2010
Updated 21 Dec 2010
Type Journal
Year 1998
Where APIN
Authors Sung-Bae Cho, Katsunori Shimohara
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