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European Conference on Genetic Programming

EuroGP 1998: Genetic Programming pp 97–112Cite as

Genetic programming bloat with dynamic fitness

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1391))

Abstract

In artificial evolution individuals which perform as their parents are usually rewarded identically to their parents. We note that Nature is more dynamic and there may be a penalty to pay for doing the same thing as your parents. We report two sets of experiments where static fitness functions are firstly augmented by a penalty for unchanged offspring and secondly the static fitness case is replaced by randomly generated dynamic test cases. We conclude genetic programming, when evolving artificial ant control programs, is surprisingly little effected by large penalties and program growth is observed in all our experiments.

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References

  1. Peter John Angeline. Genetic programming and emergent intelligence. In Kenneth E. Kinneax, Jr., editor, Advances in Genetic Programming, chapter 4, pages 75–98. MIT Press, 1994.

    Google Scholar 

  2. John R. Koza. Genetic Programming: On the Programming of Computers by Natural Selection. MIT Press, Cambridge, MA, USA, 1992.

    Google Scholar 

  3. John R. Koza. Genetic Programming II: Automatic Discovery of Reusable Programs. MIT Press, Cambridge Massachusetts, May 1994.

    Google Scholar 

  4. W. B. Langdon. Evolving data structures using genetic programming. In L. Eshelman, editor, Genetic Algorithms: Proceedings of the Sixth International Conference (ICGA95), pages 295–302, 1995. Morgan Kaufmann.

    Google Scholar 

  5. W. B. Langdon. Fitness causes bloat in variable size representations. Technical Report CSRP-97-14, University of Birmingham, School of Computer Science, 14 May 1997. Position paper at the Workshop on Evolutionary Computation with Variable Size Representation at ICGA-97.

    Google Scholar 

  6. W. B. Langdon. Data Structures and Genetic Programming. Kulwer, 1998.

    Google Scholar 

  7. W. B. Langdon. The evolution of size in variable length representations. In 1998 IEEE International Conference on Evolutionary Computation, Anchorage, Alaska, USA, 5–9 May 1998. Forthcomming.

    Google Scholar 

  8. W. B. Langdon and R. Poli. Fitness causes bloat. In P. K. Chawdhry et al, editors, Second On-line World Conference on Soft Computing in Engineering Design and Manufacturing. Springer-Verlag London, 23–27 June 1997.

    Google Scholar 

  9. W. B. Langdon and R. Poli. Fitness causes bloat: Mutation. This volume.

    Google Scholar 

  10. W. B. Langdon and R. Poli. Why ants are hard. Technical Report CSRP-98-4, University of Birmingham, School of Computer Science, January 1998.

    Google Scholar 

  11. Peter Nordin and Wolfgang Banzhaf. Complexity compression and evolution. In L. Eshelman, editor, Genetic Algorithms: Proceedings of the Sixth International Conference (ICGA95), pages 310–317, 1995. Morgan Kaufmann.

    Google Scholar 

  12. George R. Price. Selection and covariance. Nature, 227, August 1:520–521, 1970.

    Article  Google Scholar 

  13. Terence Soule, James A. Foster, and John Dickinson. Code growth in genetic programming. In John R. Koza, et al, editors, Genetic Programming 1996: Proceedings of the First Annual Conference, pages 215–223, 1996. MIT Press.

    Google Scholar 

  14. Walter Alden Tackett. Genetic programming for feature discovery and image discrimination. In Stephanie Forrest, editor, Proceedings of the 5th International Conference on Genetic Algorithms, ICGA-93, pages 303–309, University of Illinois at Urbana-Champaign, 17–21 July 1993. Morgan Kaufmann.

    Google Scholar 

  15. Walter Alden Tackett. Recombination, Selection, and the Genetic Construction of Computer Programs. PhD thesis, University of Southern California, Department of Electrical Engineering Systems, 1994.

    Google Scholar 

  16. Walter Alden Tackett. Greedy recombination and genetic search on the space of computer programs. In L. D. Whitley and M. D. Vose, editors, Foundations of Genetic Algorithms 3, pages 271–297, 1995. Morgan Kaufmann.

    Google Scholar 

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Authors and Affiliations

  1. School of Computer Science, University of Birmingham, B15 2TT, Birmingham, UK

    W. B. Langdon & R. Poli

Authors
  1. W. B. Langdon
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  2. R. Poli
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Editor information

Wolfgang Banzhaf Riccardo Poli Marc Schoenauer Terence C. Fogarty

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© 1998 Springer-Verlag Berlin Heidelberg

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Langdon, W.B., Poli, R. (1998). Genetic programming bloat with dynamic fitness. In: Banzhaf, W., Poli, R., Schoenauer, M., Fogarty, T.C. (eds) Genetic Programming. EuroGP 1998. Lecture Notes in Computer Science, vol 1391. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0055931

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  • DOI: https://doi.org/10.1007/BFb0055931

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-64360-9

  • Online ISBN: 978-3-540-69758-9

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