Skip to main content

Evolution of Robustness in an Electronics Design

  • Conference paper
  • First Online:
Evolvable Systems: From Biology to Hardware (ICES 2000)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1801))

Included in the following conference series:

Abstract

Evolutionary algorithms can design electronic circuits that conventional design methods cannot, because they can craft an emergent behaviour without the need for a detailed model of how the behaviours of the components affect the overall behaviour. However, the absence of such a model makes the achievement of robustness to variations in temperature, fabrication, etc., challenging. An experiment is presented showing that a robust design can be evolved without having to resort to conventional restrictive design constraints, by testing in different conditions during evolution. Surprisingly, the result tentatively suggests that even within the domain of robust digital design, evolution can explore beyond the scope of conventional methods.

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. P. Cariani. Emergence and artificial life. In C. G. Langton, C. Taylor, J. D. Farmer, and S. Rasmussen, Eds, Artificial Life II, pp. 775–797. Addison Wesley Longman, 1992.

    Google Scholar 

  2. J. P. Crutchfield and M. Mitchell. The evolution of emergent computation. Proc. Nat. Acad. Sci. USA, 92(23):10742–10746, 1995.

    Article  MATH  Google Scholar 

  3. S. Forrest. Emergent computation — self-organizing, collective, and cooperative phenomena in natural and artificial computing networks. Physica D, 42(1–3):1–11, 1990.

    Article  MathSciNet  Google Scholar 

  4. I. Harvey and A. Thompson. Through the labyrinth evolution finds a way: A silicon ridge. In T. Higuchi and M. Iwata, Eds, Proc. 1st Int. Conf. on Evolvable Systems (ICES’96), vol. 1259 of LNCS, pp. 406–422. Springer-Verlag, 1997.

    Google Scholar 

  5. J. R. Koza, F. H. Bennett III, M. A. Keane, et al. Searching for the impossible using genetic programming. In W. Banzhaf, J. Daida, A. E. Eiben, et al., Eds, Proc. Genetic and Evolutionary Computation conference (GECCO-99), pp. 1083–1091. Morgan Kaufmann, 1999.

    Google Scholar 

  6. J. Maynard Smith. Evolutionary Genetics. Oxford University Press, 1989.

    Google Scholar 

  7. I. Rechenberg. Cybernetic solution path of an experimental problem. Royal Aircraft Establishment, Library Translation 1122, 1965. Reprinted in ‘Evolutionary Computation — The fossil record’, D. B. Fogel, Ed., chap. 8, pp. 297–309, IEEE Press 1998.

    Google Scholar 

  8. H.-P. Schwefel and G. Rudolph. Contemporary evolution strategies. In F. Morán, A. Moreno, J. J. Merelo, and P. Chacon, Eds, Advances in Artificial Life: Proc. 3rd Eur. Conf. on Artificial Life, vol. 929 of LNAI, pp. 893–907. Springer-Verlag, 1995.

    Google Scholar 

  9. A. Thompson. Silicon evolution. In J. R. Koza, D. E. Goldberg, D. B. Fogel, and R. L. Riolo, Eds, Genetic Programming 1996: Proc. 1st Annual Conf. (GP96), pp. 444–452. Cambridge, MA: MIT Press, 1996.

    Google Scholar 

  10. A. Thompson. Temperature in natural and artificial systems. In P. Husbands and I. Harvey, Eds, Proc. 4th Eur. Conf. on Artificial Life (ECAL’97), pp. 388–397. MIT Press, 1997.

    Google Scholar 

  11. A. Thompson. Exploring beyond the scope of human design: Automatic generation of FPGA configurations through artificial evolution (Keynote). In Proc. 8th Annual Advanced PLD & FPGA Conference, pp. 5–8. Miller Freeman, 12th May 1998. Ascot, UK.

    Google Scholar 

  12. A. Thompson. On the automatic design of robust electronics through artificial evolution. In M. Sipper, D. Mange, and A. Pérez-Uribe, Eds, Proc. 2nd Int. Conf. on Evolvable Systems (ICES’98), vol. 1478 of LNCS, pp. 13–24. Springer-Verlag, 1998.

    Google Scholar 

  13. A. Thompson, P. Layzell, and R. S. Zebulum. Explorations in design space: Unconventional electronics design through artificial evolution. IEEE Trans. Evol. Comp., 3(3):167–196, 1999.

    Article  Google Scholar 

  14. Xilinx. Packages and thermal characteristics V1.2, August 1996. In The Programmable Logic Data Book, chapter 10. Xilinx, Inc., 1996.

    Google Scholar 

  15. Xilinx. XC6200 field programmable gate arrays. Data Sheet, Xilinx, Inc., April 1997. Version 1.10.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2000 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Thompson, A., Layzell, P. (2000). Evolution of Robustness in an Electronics Design. In: Miller, J., Thompson, A., Thomson, P., Fogarty, T.C. (eds) Evolvable Systems: From Biology to Hardware. ICES 2000. Lecture Notes in Computer Science, vol 1801. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-46406-9_22

Download citation

  • DOI: https://doi.org/10.1007/3-540-46406-9_22

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-67338-5

  • Online ISBN: 978-3-540-46406-8

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics