Skip to main content

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 167))

Summary

Memory plays an important part in the development of the collective and individual fitness of a biological species. Knowledge acquired by teaching and experience is stored in memory and retrieved when an individual is required to perform a task or solve a problem. In this article we discuss the concept of memory in a genetic programming (GP) system. The memory operator we introduce is used in conjunction with, and in support of, the traditional selection, crossover, and mutation operators. We implement a form of memory by preserving the component parts of good designs from previous generations. The memory is used as a pool of genetic material which is introduced into later generations by a form of mutation. It thus acts as a ’tribal folklore’ or cultural memory for the system. Using the memory operator, significant improvements in performance can be achieved on some problems. We believe that these improvements may be achievable in most areas in which Genetic Programming is applied, given suitable encodings, fitness measures and parameter tuning.

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 169.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover 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. Holland J. Adaptation in natural and artificial systems. University of Michigan Press, 1975.

    Google Scholar 

  2. Koza J. Genetic programming: On the programming of computers by means of natural selection. MIT Press, 1992.

    MATH  Google Scholar 

  3. Koza J. Genetic programming II: Automatic discovery of reusable programs. MIT Press, 1994.

    MATH  Google Scholar 

  4. Bonner JT. The Evolution of Culture in Animals. Princeton University Press, 1980.

    Google Scholar 

  5. Spector L and Luke S. Culture enhances the evolvability of cognition. In Proceedings of the Eighteenth Annual Conference of the Cognitive Science Society, pages 672–677, Mahwah, NJ, 1996. Lawrence Erlbaum Associates.

    Google Scholar 

  6. Angeline PJ and Pollack JB, editors. Proceedings of the 5th International Conference on Genetic Algorithms, San Francisco, 1993. Morgan Kaufmann.

    Google Scholar 

  7. Dawkins R. The Selfish Gene. Oxford University Press, 1976.

    Google Scholar 

  8. Banzhaff W, Nordin P, Keller E, and Francone FD. Genetic Programming. Morgan Kaufmann, San Francisco, 1998.

    Book  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2005 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Bearpark, K., Keane, A.J. (2005). The Use of Collective Memory in Genetic Programming. In: Jin, Y. (eds) Knowledge Incorporation in Evolutionary Computation. Studies in Fuzziness and Soft Computing, vol 167. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-44511-1_2

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-44511-1_2

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-06174-5

  • Online ISBN: 978-3-540-44511-1

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics