Skip to main content

What Basis for Genetic Dynamics?

  • Conference paper
Genetic and Evolutionary Computation – GECCO 2004 (GECCO 2004)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3102))

Included in the following conference series:

Abstract

We present a covariant form for genetic dynamics and show how different formulations are simply related by linear coordinate transformations. In particular, in the context of the simple genetic algorithm, we show how the Vose model, in either the string or Walsh bases, is related to recent coarse-grained formulations that are naturally interpreted in terms of the Building Block basis (BBB). We also show that the latter is dual to the Taylor basis. The tensor product structure of the dynamical equations is analyzed, permitting the factorization of the N-bit operators in 1-bit factors.

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, New York (2002)

    MATH  Google Scholar 

  2. Stephens, C.R., Poli, R.: E C theory - in theory: Towards a unification of evolutionary computation theory. In: Menon, A. (ed.) Frontiers of Evolutionary Computation, pp. 129–156. Kluwer Academic Publishers, Dordrecht (2004)

    Chapter  Google Scholar 

  3. Stephens, C.R., Zamora, A.: EC theory: A unified viewpoint. In: Cantú-Paz, E., Foster, J.A., Deb, K., Davis, L., Roy, R., O’Reilly, U.-M., Beyer, H.-G., Kendall, G., Wilson, S.W., Harman, M., Wegener, J., Dasgupta, D., Potter, M.A., Schultz, A., Dowsland, K.A., Jonoska, N., Miller, J., Standish, R.K. (eds.) GECCO 2003. LNCS, vol. 2723, pp. 1394–1402. Springer, Heidelberg (2003)

    Chapter  Google Scholar 

  4. Vose, M.D.: The simple genetic algorithm: Foundations and theory. MIT Press, Cambridge (1999)

    MATH  Google Scholar 

  5. Stephens, C.R., Waelbroeck, H.: Schemata evolution and building blocks. Evol. Comp. 7, 109–124 (1999)

    Article  Google Scholar 

  6. Poli, R.: Exact schema theory for genetic programming and variable-length genetic algorithms with one-point crossover. Genetic Programming and Evolvable Machines 2(2), 123–163 (2001)

    Article  MATH  MathSciNet  Google Scholar 

  7. Stephens, C.R., Waelbroeck, H.: Effective degrees of freedom of genetic algorithms and the block hypothesis. In: Bäck, T. (ed.) Proceedings of ICGA 1997, San Francisco, CA, pp. 31–41. Morgan Kaufmann, San Francisco (1997)

    Google Scholar 

  8. Stephens, C.R.: The renormalization group and the dynamics of genetic systems. Acta Phys. Slov. 52, 515–524 (2003)

    Google Scholar 

  9. Akivis, M.A., Goldberg, V.V.: An Introduction to Linear Algebra and Tensors. Dover Publications, Mineola (1977)

    Google Scholar 

  10. Weinberger, E.D.: Fourier and Taylor series on fitness landscapes. Biological Cybernetics 65, 321–330 (1991)

    Article  MATH  Google Scholar 

  11. Wright, A.H.: The exact schema theorem (January 2000), http://www.cs.umt.edu/CS/FAC-/WRIGHT/papers/schema.pdf

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2004 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Chryssomalakos, C., Stephens, C.R. (2004). What Basis for Genetic Dynamics?. In: Deb, K. (eds) Genetic and Evolutionary Computation – GECCO 2004. GECCO 2004. Lecture Notes in Computer Science, vol 3102. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24854-5_101

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-24854-5_101

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-22344-3

  • Online ISBN: 978-3-540-24854-5

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics