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An Indirect Block-Oriented Representation for Genetic Programming

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Genetic Programming (EuroGP 2001)

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Abstract

When Genetic Programming (GP) is applied to system identification or controller design different codings can be used for internal representation of the individuals. One common approach is a block-oriented representation where nodes of the tree structure directly correspond to blocks in a block diagram. In this paper we present an indirect block-oriented representation, which adopts some aspects of the way humans perform the modelling in order to increase the GP system’s performance. A causality measure based on an edit distance is examined to compare the direct an the indirect representation. Finally, results from a real world application of the indirect block-oriented representation are presented.

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Author information

Authors and Affiliations

  1. Institute for Automatic Control, Landgraf-Georg-Str. 4, D, 64283, Darmstadt, Germany

    Eva Brucherseifer, Peter Bechtel & Peter Marenbach

  2. BASF AG, Process Engineering Life Sciences, ZHV A015, 67056, Ludwigshafen

    Stephan Freyer

Authors
  1. Eva Brucherseifer
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  2. Peter Bechtel
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  3. Stephan Freyer
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  4. Peter Marenbach
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Editor information

Editors and Affiliations

  1. School of Computer Science, University of Birmingham, Birmingham

    Julian Miller

  2. Computer Science Institute, University of Lausanne, Lausanne

    Marco Tomassini

  3. Dipartimento di Elettronica e Informazione, Politecnico di Milano, Italy

    Pier Luca Lanzi

  4. Computer Science and Information Systems, University of Limerick, Limerick

    Conor Ryan

  5. Dipartimento di Tecnologie dell’Informazione, Università degli Studi di Milano, Italy

    Andrea G. B. Tettamanzi

  6. Department of Computer Science, University College London, London

    William B. Langdon

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© 2001 Springer-Verlag Berlin Heidelberg

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Brucherseifer, E., Bechtel, P., Freyer, S., Marenbach, P. (2001). An Indirect Block-Oriented Representation for Genetic Programming. In: Miller, J., Tomassini, M., Lanzi, P.L., Ryan, C., Tettamanzi, A.G.B., Langdon, W.B. (eds) Genetic Programming. EuroGP 2001. Lecture Notes in Computer Science, vol 2038. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45355-5_21

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  • DOI: https://doi.org/10.1007/3-540-45355-5_21

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-41899-3

  • Online ISBN: 978-3-540-45355-0

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