Skip to main content
SpringerLink
Log in

Developmental Models for Emergent Computation

  • Conference paper
  • First Online:
Evolvable Systems: From Biology to Hardware (ICES 2003)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2606))

Included in the following conference series:

Abstract

The developmental metaphor has clear advantages for the design of physically-realizable artifacts, particularly when coupled with evolutionary algorithms. However, the embodiment of a developmental process in a purely computational system appears much more problematic, largely because embryogenesis evolved for the purpose of synthesizing 3-dimensional structure from a linear code, not for growing Universal Turing Machines.

This research considers possible models of computational problem-solving based on the 5 primary developmental stages: cleavage division, patterning, cell differentiation, morphogenesis, and growth. A specific developmental approach to the NP-Complete problem, vertex cover (VC), is discussed, as well as a general model of developmental computation based on a multicellular extension of PUSH [12], a new stack-based language designed specifically for evolutionary computation.

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

Access this chapter

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 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. J. Astor and C. Adami, A developmental model for the evolution of artificial neural networks, Artificial Life, 6 (2000), pp. 189–218.

    Article  Google Scholar 

  2. M. Dorigo, V. Maniezzo, and A. Colorni, Ant system: Optimization by a colony of cooperating agents, IEEE Trans. on Systems, Man, and Cybernetics-Part B, 26 (1996), pp. 29–41.

    Article  Google Scholar 

  3. C. Furusawa and K. Kaneko, Complex organization in multicellularity as a necessity in evolution, Artificial Life, 6 (2000), pp. 265–282.

    Article  Google Scholar 

  4. M. Garey and D. Johnson, Computers and Intractability: A Guide to the Theory of NP-Completeness, W.H. Freeman and Company, San Francisco, 1979.

    MATH  Google Scholar 

  5. S. Hofmeyr and S. Forrest, Architecture for an artificial immune system, Evolutionary Computation, 7 (2000), pp. 1289–1296.

    Google Scholar 

  6. J. H. Holland, Adaptation in Natural and Artificial Systems, The MIT Press, Cambridge, MA, 2 ed., 1992.

    Google Scholar 

  7. H. Kitano, Designing neural networks using genetic algorithms with graph generation system, Complex Systems, 4 (1990), pp. 461–476.

    MATH  Google Scholar 

  8. J. R. Koza, Genetic Programming: On the Programming of Computers by Natural Selection, MIT Press, Cambridge, MA, 1992.

    MATH  Google Scholar 

  9. W. McCulloch and W. Pitts, A logical calculus of the ideas immanent in nervous activity, Bulletin of Mathematical Biophysics, 5 (1943), pp. 115–133.

    Article  MATH  MathSciNet  Google Scholar 

  10. D. J. Montana, Strongly typed genetic programming, Evolutionary Computation, 3 (1995), pp. 199–230.

    Article  Google Scholar 

  11. D. E. Moriarty and R. Miikkulainen, Forming neural networks through efficient and adaptive coevolution, Evolutionary Computation, 5 (1997), pp. 373–399.

    Article  Google Scholar 

  12. L. Spector and A. Robinson, Genetic programming and autoconstructive evolution with the push programming language, Genetic Programming and Evolvable Machines, 3 (2002), pp. 7–40.

    Article  MATH  Google Scholar 

  13. K. Stanley and R. Miikkulainen, Evolving neural networks through augmenting topologies, Evolutionary Computation, 10 (2002), pp. 99–127.

    Article  Google Scholar 

  14. A. Stauffer, D. Mange, G. Tempesti, and C. Teuscher, A self-repairing and self-healing electronic watch: The biowatch, in Lecture Notes in Computer Science, Y. Liu, K. Tanaka, M. Iwata, T. Higuchi, and M. Yasunaga, eds., vol. 2210, Berlin, 1998, Springer-Verlag, pp. 112–127.

    Google Scholar 

  15. H. Takagi, K. Kaneko, and T. Yomo, Evolution of genetic codes through isologous diversification of cellular states, Artificial Life, 6 (2000), pp. 283–306.

    Article  Google Scholar 

  16. L. Wolpert, Principles of Development, Oxford University Press, New York, 2002.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. The Norwegian University of Science and Technology, Trondheim, Norway

    Keith L. Downing

Authors
  1. Keith L. Downing
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. The Department of Electronics, The University of York, YO10 5DD, Heslington, York, United Kingdom

    AAndy M. Tyrrell

  2. Department of Computer and Information Science, The Norwegian University of Science and Technology, Sem Sælands Vei, 7491, Trondheim, Norway

    Pauline C. Haddow

  3. Department of Informatics, University of Oslo, P.O. Box 1080, 0316, Blindern, Oslo, Norway

    Jim Torresen

Rights and permissions

Reprints and permissions

Copyright information

© 2003 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Downing, K.L. (2003). Developmental Models for Emergent Computation. In: Tyrrell, A.M., Haddow, P.C., Torresen, J. (eds) Evolvable Systems: From Biology to Hardware. ICES 2003. Lecture Notes in Computer Science, vol 2606. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36553-2_10

Download citation

  • DOI: https://doi.org/10.1007/3-540-36553-2_10

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-00730-2

  • Online ISBN: 978-3-540-36553-2

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Search

Navigation