Complexifying Artificial Neural Networks through Topological
نویسندگان
چکیده
This paper describes a novel way of complexifying artificial neural networks through topological reorganization. The neural networks are reorganized to optimize their neural complexity, which is a measure of the information-theoretic complexity of the network. Complexification of neural networks here happens through rearranging connections, i.e. removing one or more connections and placing them elsewhere. The results verify, that a structural reorganization can help to increase the probability of discovering a neural network capable of adequately solving complex tasks. The networks and the methodology proposed are tested in a simulation of a mobile robot racing around a track.
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تاریخ انتشار 2008