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Incremental growth in modular neural networks.

MacLeod, Christopher; Maxwell, Grant; Muthuraman, Sethuraman


Christopher MacLeod

Grant Maxwell

Sethuraman Muthuraman


This paper outlines an algorithm for incrementally growing Artificial Neural Networks. The algorithm allows the network to expand by adding new sub-networks or modules to an existing structure; the modules are trained using an Evolutionary Algorithm. Only the latest module added to the network is trained, the previous structure remains fixed. The algorithm allows information from different data domains to be integrated into the network and because the search space in each iteration is small, large and complex networks with a modular structure can emerge naturally. The paper describes an application of the algorithm to a legged robot and discusses its biological inspiration.

Journal Article Type Article
Publication Date Jun 30, 2009
Journal Engineering applications of artificial intelligence
Print ISSN 0952-1976
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 22
Issue 4-5
Pages 660-666
Institution Citation MACLEOD, C., MAXWELL, G. and MUTHURAMAN, S. 2009. Incremental growth in modular neural networks. Engineering applications of artificial intelligence [online], 22(4-5), pages 660-666. Available from:
Keywords Genetic algorithm; Modular artificial neural network; Robotics; Incremental growth; Incremental evolution; Evolutionary algorithm


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