Neutral Emergence and Coarse Graining

  • Andrew Weeks
  • Susan Stepney
  • Fiona Polack
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4648)

Abstract

We introduce the concept of neutral emergence (defined by analogy to an information theoretic view of neutral evolution), and discuss how it might be used in the engineering of robust emergent systems. We describe preliminary results from an application to coarse graining of cellular automata.

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References

  1. 1.
    Adami, C.: Introduction to Artificial Life. Springer, Heidelberg (1998)MATHGoogle Scholar
  2. 2.
    Adami, C.: What is complexity? BioEssays 24, 1085–1094 (2002)CrossRefGoogle Scholar
  3. 3.
    Adami, C., Cerf, N.J.: Physical complexity of symbolic sequences. Physica D 137, 62–69 (2000)MATHCrossRefGoogle Scholar
  4. 4.
    Bar-Yam, Y.: A mathematical theory of strong emergence using multiscale variety. Complexity 9(6), 15–24 (2004)CrossRefGoogle Scholar
  5. 5.
    Berlekamp, E.R., Conway, J.H., Guy, R.K.: Winning Ways for your Mathematical Plays. Academic Press, London (1982)MATHGoogle Scholar
  6. 6.
    Clark, J.A., Stepney, S., Chivers, H.: Breaking the model: finalisation and a taxonomy of security attacks. ENTCS 137(2), 225–242 (2005)Google Scholar
  7. 7.
    Israeli, N., Goldenfeld, N.: Coarse-graining of cellular automata, emergence, and the predictability of complex systems. Phys. Rev. E 73, 026203 (2006)Google Scholar
  8. 8.
    Kauffman, S.A.: The Origins of Order: self-organization and selection in evolution. Oxford University Press, Oxford (1993)Google Scholar
  9. 9.
    Kauffman, S.A.: At Home in the Universe. Oxford University Press, Oxford (1995)Google Scholar
  10. 10.
    Langton, C.G.: Computation at the Edge of Chaos: Phase-Transitions and Emergent Computation. PhD thesis, University of Michigan (1991)Google Scholar
  11. 11.
    Mitchell, M., Crutchfield, J.P., Hraber, P.T.: Dynamics, computation, and the ‘edge of chaos’: a re-examination. In: Cowan, G.A., et al. (eds.) Complexity: Metaphors, Models, and Reality, pp. 497–513. Addison-Wesley, Reading (1994)Google Scholar
  12. 12.
    Ray, A.: Symbolic dynamic analysis of complex systems for anomoly detection. Signal Processing 84, 1115–1130 (2004)CrossRefGoogle Scholar
  13. 13.
    Ronald, E.M.A., Sipper, M., Capcarrère, M.S.: Testing for emergence in artificial life. In: Floreano, D., Mondada, F. (eds.) ECAL 1999. LNCS, vol. 1674, pp. 13–20. Springer, Heidelberg (1999)Google Scholar
  14. 14.
    Shalizi, C.R.: Causal architecture, complexity and self-organization in time series and cellular automata. PhD thesis, University of Wisconsin at Madison (2001)Google Scholar
  15. 15.
    Stearns, S.C., Hoekstra, R.F.: Evolution: an introduction. OUP, Oxford (2000)Google Scholar
  16. 16.
    Stepney, S., Polack, F., Turner, H.: Engineering emergence. In: ICECCS 2006, IEEE Computer Society Press, Los Alamitos (2006)Google Scholar
  17. 17.
    Takens, F.: Detecting strange attractors in turbulence. In: Rand, D.A., Young, L.-S. (eds.) Dynamical Systems and Turbulence, pp. 230–242. Springer, Heidelberg (1981)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Andrew Weeks
    • 1
  • Susan Stepney
    • 1
  • Fiona Polack
    • 1
  1. 1.Department of Computer Science, University of YorkUK

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