Abstract
In this paper we propose a biological inspired model to develop the structure of artificial neural networks. The model is based on an artificial genetic: regualtory system, which controls the development of the neural network. The model allows for different cell types which are the result of different intercellular communication processes. Different cell types will also lead to different connection patterns of the neural networks. The goal of the proposed model is to investigate the question how the local genetic: processes are able to construct the structure of a neural network.
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© 1997 Springer-Verlag Berlin Heidelberg
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Eggenberger, P. (1997). Creation of neural networks based on developmental and evolutionary principles. In: Gerstner, W., Germond, A., Hasler, M., Nicoud, JD. (eds) Artificial Neural Networks — ICANN'97. ICANN 1997. Lecture Notes in Computer Science, vol 1327. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0020177
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DOI: https://doi.org/10.1007/BFb0020177
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