Agent-based Evolution of Neural Network Architecture

A. Byrski, M. Kisiel-Dorohinicki, and E. Nawarecki (Poland)



In the paper an agent-based approach to evolutionary optimisation of a neural network architecture is presented. A concept of decentralised evolutionary computation realised as an evolutionary multi-agent system (EMAS) may help to avoid some of the shortcommings of classical evolutionary optimisation techniques. General considerations are illustrated by the particular system dedicated to a problem of time-series prediction. Selected experimental results conclude the work.

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