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Creation of neural networks based on developmental and evolutionary principles

  • Part I: Coding and Learning in Biology
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Artificial Neural Networks — ICANN'97 (ICANN 1997)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1327))

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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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Authors and Affiliations

  1. AILab and Software Engineering Department of Computer Science, University of Zurich, Winterthurerstrasse190, 8057, Zurich, Switzerland

    Peter Eggenberger

Authors
  1. Peter Eggenberger
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Editor information

Wulfram Gerstner Alain Germond Martin Hasler Jean-Daniel Nicoud

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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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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-63631-1

  • Online ISBN: 978-3-540-69620-9

  • eBook Packages: Springer Book Archive

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