Biological metaphors and the design of modular artificial neural networks
Egbert J. W. Boers, Herman Kuiper, Bart L.M. Happel, Egbert J. W. Boers · 2010
In this thesis, a method is proposed with which good modular artificial neural network structures can be found automatically using a computer program. A number of biological metaphors are incorporated in the method. It will be argued that modular artificial neural networks have a better performance than their non-modular counterparts. The human brain can also be seen as a modular neural network, and the proposed search method is based on the natural process that resulted in the brain: Genetic algorithms are used to imitate evolution, and L-systems are used to model the kind of recipes nature uses in biological growth. A small number of experiments have been done to investigate the possibilities of the method. Preliminary results show that the method does find modular networks, and that those networks outperform `standard' solutions. The method looks very promising, although the experiments done were too limited to draw any general conclusions. One drawback is the large amount of compu...