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Computational Complexity, Genetic Programming, and Implications

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Genetic Programming (EuroGP 2001)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2038))

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Abstract

Recent theory work has shown that a Genetic Program (GP) used to produce programs may have output that is bounded above by the GP itself [l]. This paper presents proofs that show that 1) a program that is the output of a GP or any inductive process has complexity that can be bounded by the Kolmogorov complexity of the originating program; 2) this result does not hold if the random number generator used in the evolution is a true random source; a nd 3) an optimization problem being solved with a GP will have a complexity that can be bounded below by the growth rate of the minimum length problem representation used for the implementation. These results are then used to provide guidance for GP implementation.

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Author information

Authors and Affiliations

  1. Initiative for Bioinformatics and Evolutionary Studies (IBEST) Department of Computer Science, University of Idaho, Moscow, Idaho, 83844-1014, USA

    Bart Rylander, Terry Soule & James Foster

Authors
  1. Bart Rylander
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  2. Terry Soule
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  3. James Foster
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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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Rylander, B., Soule, T., Foster, J. (2001). Computational Complexity, Genetic Programming, and Implications. 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_28

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  • DOI: https://doi.org/10.1007/3-540-45355-5_28

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-41899-3

  • Online ISBN: 978-3-540-45355-0

  • eBook Packages: Springer Book Archive

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