An objective measure to compare some Automatic Generation Methods of NNArchitectures

Abstract

Many methods to codify artificial neural networks have been developed to avoid the defects of direct encoding schema, improving the search into the solution's space. A method to evaluate how the search space is covered and how movement along the search process applying genetic operators is needed in order to evaluate the different encoding strategies for a kind of artificial neural networks, feedforward neural networks. A first step of this method is considered with two encoding strategies, a direct encoding method and an indirect encoding scheme based on cellular automata.