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Designing neural networks by adaptively building blocks in cascades

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Parallel Problem Solving from Nature — PPSN III (PPSN 1994)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 866))

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Abstract

We present a novel approach for the structuring of artificial neural networks by an Evolutionary Algorithm. The structuring problem is discussed as an example of a pseudo-boolean optimization problem. The continuous Evolution Strategy is extended by an individual developmental process, in our case a stochastic generation scheme, to allow the use of adaptive genetic operators. On exemplary tests we analyze the performance and evaluate the efficiency of this approach.

Supported by the Bundesministerium für Forschung und Technologie (BMFT) grant SALGON (No. 01 IN 107).

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Authors and Affiliations

  1. Bionik und Evolutionstechnik, Technische Universität Berlin, Ackerstraße 71-76 (ACK1), D-13355, Berlin

    J. Born, I. Santibáñez-Koref & H. -M. Voigt

Authors
  1. J. Born
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  2. I. Santibáñez-Koref
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  3. H. -M. Voigt
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Editor information

Yuval Davidor Hans-Paul Schwefel Reinhard Männer

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© 1994 Springer-Verlag Berlin Heidelberg

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Born, J., Santibáñez-Koref, I., Voigt, H.M. (1994). Designing neural networks by adaptively building blocks in cascades. In: Davidor, Y., Schwefel, HP., Männer, R. (eds) Parallel Problem Solving from Nature — PPSN III. PPSN 1994. Lecture Notes in Computer Science, vol 866. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-58484-6_290

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  • DOI: https://doi.org/10.1007/3-540-58484-6_290

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-58484-1

  • Online ISBN: 978-3-540-49001-2

  • eBook Packages: Springer Book Archive

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