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Memetic Cooperative Co-evolutionary Recurrent Neural Networks

Chandra, Rohitash and Frean, M. and Zhang, M. (2011) Memetic Cooperative Co-evolutionary Recurrent Neural Networks. Soft Computing, N/A . N/A-N/A. ISSN 1432-7643

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Abstract

Adaptation during evolution has been an important focus of research in training neural networks. Cooperative coevolution has played a significant role in improving standard evolution of neural networks by organizing the training problem into modules and independently solving them. The number of modules required to represent a neural network is critical to the success of evolution. This paper proposes a framework for the adaptation of the number of modules during evolution. The framework is called adaptive modularity cooperative coevolution. It is used for training recurrent neural networks on grammatical inference problems. The results shows that the proposed approach performs better than its counterparts as the dimensionality of the problem increases.

Item Type: Journal Article
Subjects: Q Science > Q Science (General)
Divisions: Faculty of Science, Technology and Environment (FSTE) > School of Computing, Information and Mathematical Sciences
Depositing User: Repo Editor
Date Deposited: 15 May 2015 11:33
Last Modified: 15 May 2015 11:33
URI: http://repository.usp.ac.fj/id/eprint/7979
UNSPECIFIED

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