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Fighting Program Bloat with the Fractal Complexity Measure

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Book cover Genetic Programming (EuroGP 2000)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1802))

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Abstract

The problem of evolving decision programs to be used for medical diagnosis prediction brought us to the problem, well know to the genetic programming (GP) community the tendency of programs to grow in length too fast. While searching for a solution we found out that an appropriately defined fractal complexity measure can differentiate between random and non-random computer programs by measuring the fractal structure of the computer programs. Knowing this fact, we introduced the fractal measure α in the evaluation and selection phase of the evolutionary process of decision program induction, which resulted in a significant program bloat reduction.

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Author information

Authors and Affiliations

  1. Laboratory for System Design, University of Maribor – FERI, Smetanova 17, SI-2000, Maribor, Slovenia

    Vili Podgorelec & Peter Kokol

Authors
  1. Vili Podgorelec
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  2. Peter Kokol
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Editor information

Editors and Affiliations

  1. Department of Computing and Electronic Systems, University of Essex, Wivenhoe Park, CO4 3SQ, Colchester, UK

    Riccardo Poli

  2. Department of Computer Science, Memorial University of Newfoundland, Canada

    Wolfgang Banzhaf

  3. Departments of Mathematical, Biological Sciences and Computing and Electronic Systems, University of Essex, UK

    William B. Langdon

  4. School of Computer Science, The University of Birmingham, B15 2TT, Edgbaston, Birmingham, UK

    Julian Miller

  5. Dept. of Physical Rescource Theory, Chalmers University of Technology, 412 96, Göteborg, Sweden

    Peter Nordin

  6. School of Computing, Information Systems and Mathematics, South Bank University, SE1 0AA, London, UK

    Terence C. Fogarty

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© 2000 Springer-Verlag Berlin Heidelberg

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Podgorelec, V., Kokol, P. (2000). Fighting Program Bloat with the Fractal Complexity Measure. In: Poli, R., Banzhaf, W., Langdon, W.B., Miller, J., Nordin, P., Fogarty, T.C. (eds) Genetic Programming. EuroGP 2000. Lecture Notes in Computer Science, vol 1802. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-46239-2_25

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  • DOI: https://doi.org/10.1007/978-3-540-46239-2_25

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-67339-2

  • Online ISBN: 978-3-540-46239-2

  • eBook Packages: Springer Book Archive

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