Evolutionary artificial neural networks

We present experiments which show that a genetic algorithm (GA) can effectively search for a set of local feature detectors, which can be used by higher neural network layers to perform an image classification task. Three different methods of encoding hidden unit weights into the GA are presented, including one which coevolves all the feature detectors in a single chromosome, and two which promote the cooperation of feature detectors by encoding them in their own chromosome. The fitness function measures the classification percentage and confidence of the networks on validation data in order to encourage generalization