Skip to main content
SpringerLink
Log in
Book cover

Asia-Pacific Conference on Simulated Evolution and Learning

SEAL 2008: Simulated Evolution and Learning pp 514–523Cite as

Evolving Digital Circuits in an Industry Standard Hardware Description Language

  • Conference paper

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5361))

Abstract

Evolutionary Meta Compilation (EMC) is a recent technique that enables unmodified external applications to seamlessly perform target program compilation and fitness evaluation for an Evolutionary Computation system. Grammatical Evolution (GE) is a method for evolving computer programs in an arbitrary programming language using a grammar specified in Backus-Naur Form. This paper combines these techniques to demonstrate the evolution of both sequential and combinational digital circuits in an Industry Standard Hardware Description Language (Verilog) using an external hardware synthesis engine and simulator. Overall results show the successful evolution of core digital circuit components. An extension to GE is also presented to attempt to increase the probability of maintaining an evolved program’s semantic integrity after crossover operations are performed. Early results show performance improvements in applying this technique to the majority of the presented test cases. It is suggested that this feature may also be considered for use in the evolution of software programs in C and other languages.

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

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   109.99
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

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Cramer, N.: A representation for the adaptive generation of simple sequential programs. In: Grefenstette, J. (ed.) Proceedings of an International Conference on Genetic Algorithms and their Applications, pp. 183–187 (1985)

    Google Scholar 

  2. Dickmans, D., Schmidhuber, J., Winklhofer, A.: Der genetische algorithmus: Eine implementierung in prolog. Technical report, Fortgeschrittenenpraktikum, Instistut f. Informatik, Lehrstuhl Prof. Radig, Tech. Univ. Munich (1987)

    Google Scholar 

  3. Koza, J.: Genetic Programming. MIT Press, Cambridge (1992)

    MATH  Google Scholar 

  4. Ryan, C., Collins, J., O’Neill, M.: Grammatical Evolution: Evolving programs for an arbitrary language. In: Banzhaf, W., Poli, R., Schoenauer, M., Fogarty, T.C. (eds.) EuroGP 1998. LNCS, vol. 1391. Springer, Heidelberg (1998)

    Chapter  Google Scholar 

  5. O’Neill, M., Ryan, C.: Grammatical Evolution: Evolutionary Automatic Programming in an Arbitrary Language. Springer, Heidelberg (2003)

    Book  MATH  Google Scholar 

  6. Miller, J.F., Job, D., Vassilev, V.K.: Principles in the evolutionary design of digital circuits - part II. Genetic Programming and Evolvable Machines 1(3), 259–288 (2000)

    Article  MATH  Google Scholar 

  7. Cullen, J.: Evolutionary Meta Compilation: Evolving programs using real world engineering tools. In: Hornby, G., Sekanina, L., Haddow, P. (eds.) Evolvable Systems: From Biology to Hardware 2008 (2008)

    Google Scholar 

  8. Harper, R., Blair, A.: A structure preserving crossover in Grammatical Evolution. In: 2005 IEEE Congress on Evolutionary Computation, pp. 2537–2544 (2005)

    Google Scholar 

  9. Knuth, D.: Semantics of context-free languages. In: Theory of Computing Systems, pp. 127–145. Springer, New York (1968)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Artificial Intelligence Laboratory, University of New South Wales, Sydney NSW, Australia

    Jamie Cullen

Authors
  1. Jamie Cullen
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. School of Computer Science and information Technology, RMIT University, VIC 3001, Melbourne, Australia

    Xiaodong Li

  2. Melbourne School Engineering, Department of Computer Science and Software Engineering, The University of Melbourne, VIC 3001, Melbourne, Australia

    Michael Kirley

  3. School of Mathematics, Statistics and Computer Science, Victoria University of Wellington, P.O. Box 600, 6140, Wellington, New Zealand

    Mengjie Zhang

  4. Faculty of Information Technology, Monash University, Clayton Campus, VIC 3800, Australia

    David Green

  5. School of Computer Science and Information Technology, RMIT University, VIC 3001, Melbourne, Australia

    Vic Ciesielski

  6. School of Information Technology and Electrical Engineering, Australian Defence Force Academy, University of New South Wales, Canberra, Australia

    Hussein Abbass

  7. School of Computer Science, University of Adelaide, SA 5005, Adelaide, Australia

    Zbigniew Michalewicz

  8. Faculty of Information and Communication Technologies, Swinburne University of Technology, Melbourne, Australia

    Tim Hendtlass

  9. Indian Institute of Technology Kanpur, Department of Mechanical Engineering, Kanpur Genetic Algorithms Laboratory (KanGAL), 208016, Kanpur, Uttar Pradesh, India

    Kalyanmoy Deb

  10. Department of Electrical and Computer Engineering, National University of Singapore, 4 Engineering Drive 3, 117576, Singapore

    Kay Chen Tan

  11. Institute AIFB, University of Karlsruhe, 76128, Karlsruhe, Germany

    Jürgen Branke

  12. Xi’an Jiaotong-Liverpool University, 215123, Suzhoum, China

    Yuhui Shi

Rights and permissions

Reprints and permissions

Copyright information

© 2008 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Cullen, J. (2008). Evolving Digital Circuits in an Industry Standard Hardware Description Language. In: Li, X., et al. Simulated Evolution and Learning. SEAL 2008. Lecture Notes in Computer Science, vol 5361. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89694-4_52

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-89694-4_52

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-89693-7

  • Online ISBN: 978-3-540-89694-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation