Skip to main content

Extending Operator Equalisation: Fitness Based Self Adaptive Length Distribution for Bloat Free GP

  • Conference paper
Book cover Genetic Programming (EuroGP 2009)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5481))

Included in the following conference series:

Abstract

Operator equalisation is a recent bloat control technique that allows accurate control of the program length distribution during a GP run. By filtering which individuals are allowed in the population, it can easily bias the search towards smaller or larger programs. This technique achieved promising results with different predetermined target length distributions, using a conservative program length limit. Here we improve operator equalisation by giving it the ability to automatically determine and follow the ideal length distribution for each stage of the run, unconstrained by a fixed maximum limit. Results show that in most cases the new technique performs a more efficient search and effectively reduces bloat, by achieving better fitness and/or using smaller programs. The dynamics of the self adaptive length distributions are briefly analysed, and the overhead involved in following the target distribution is discussed, advancing simple ideas for improving the efficiency of this new technique.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Langdon, W.B., Poli, R.: Foundations of Genetic Programming. Springer, Heidelberg (2002)

    Book  MATH  Google Scholar 

  2. Silva, S.: Controlling bloat: individual and population based approaches in genetic programming. Ph.D thesis, Dep. Informatics Engineering, Univ. Coimbra (2008)

    Google Scholar 

  3. Poli, R., Langdon, W.B., Dignum, S.: On the limiting distribution of program sizes in tree-based genetic programming. In: Ebner, M., O’Neill, M., Ekárt, A., Vanneschi, L., Esparcia-Alcázar, A.I. (eds.) EuroGP 2007. LNCS, vol. 4445, pp. 193–204. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  4. Dignum, S., Poli, R.: Generalisation of the limiting distribution of program sizes in tree-based genetic programming and analysis of its effects on bloat. In: Thierens, D., et al. (eds.) Proceedings of GECCO 2007, pp. 1588–1595. ACM Press, New York (2007)

    Google Scholar 

  5. Dignum, S., Poli, R.: Crossover, sampling, bloat and the harmful effects of size limits. In: O’Neill, M., Vanneschi, L., Gustafson, S., Esparcia Alcázar, A.I., De Falco, I., Della Cioppa, A., Tarantino, E. (eds.) EuroGP 2008. LNCS, vol. 4971, pp. 158–169. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  6. Poli, R., McPhee, N.F., Vanneschi, L.: The impact of population size on code growth in GP: analysis and empirical validation. In: Keijzer, M., et al. (eds.) Proceedings of GECCO 2008, pp. 1275–1282. ACM Press, New York (2008)

    Google Scholar 

  7. Dignum, S., Poli, R.: Operator equalisation and bloat free GP. In: O’Neill, M., Vanneschi, L., Gustafson, S., Esparcia Alcázar, A.I., De Falco, I., Della Cioppa, A., Tarantino, E. (eds.) EuroGP 2008. LNCS, vol. 4971, pp. 110–121. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  8. Silva, S., Costa, E.: Dynamic limits for bloat control in genetic programming and a review of past and current bloat theories. Genet. Program. Evolvable Mach. (January 13, 2009), http://www.springerlink.com/content/k001162572j4vh70 , doi:10.1007/s10710-008-9075-9

  9. Koza, J.R.: Genetic programming – on the programming of computers by means of natural selection. MIT Press, Cambridge (1992)

    MATH  Google Scholar 

  10. Rosca, J.P.: Generality versus Size in Genetic Programming. In: Koza, J.R., et al. (eds.) Proceedings of GP 1996, pp. 381–387. MIT Press, Cambridge (1996)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2009 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Silva, S., Dignum, S. (2009). Extending Operator Equalisation: Fitness Based Self Adaptive Length Distribution for Bloat Free GP. In: Vanneschi, L., Gustafson, S., Moraglio, A., De Falco, I., Ebner, M. (eds) Genetic Programming. EuroGP 2009. Lecture Notes in Computer Science, vol 5481. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01181-8_14

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-01181-8_14

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-01180-1

  • Online ISBN: 978-3-642-01181-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics