Skip to main content

The Emergence of Ontogenic Scaffolding in a Stochastic Development Environment

  • 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

Evolutionary designs based upon Artificial Ontogenies are beginning to cross from virtual to real environments. In such systems the evolved genotype is an indirect, procedural representation of the final structure. To date, most Artificial Ontogenies have relied upon an error-free development process to generate their phenotypic structure. In this paper we explore the effects and consequences of developmental error on Artificial Ontogenies. In a simple evolutionary design task, and using an indirect procedural representation that lacks the ability to test intermediate results of development, we demonstrate the emergence of ontogenic mechanisms which are able to cope with developmental error.

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

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

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.

Similar content being viewed by others

References

  1. Lohn, J., Crawford, J., Globus, A., Hornby, G., Kraus, W., Larchev, G., Pryor, A., Sriviastava, D.: Evolvable systems for space applications. In: International Conference on Space Mission Challenges for Information Technology, SMC-IT (2003)

    Google Scholar 

  2. Pollack, J.B., Lipson, H., Hornby, G., Funes, P.: Three generations of automatically designed robots. Artifial Life 7, 215–223 (2001)

    Article  Google Scholar 

  3. Kumar, S., Bentley, P.J.: Computational embryology: past, present and future. In: Advances in evolutionary computing: theory and applications, pp. 461–477. Springer, New York (2003)

    Google Scholar 

  4. Stanley, K.O., Miikkulainen, R.: A taxonomy for articial embryogeny. Artificial Life 9, 93–130 (2002)

    Article  Google Scholar 

  5. Jakobi, N., Husbands, P., Harvey, I.: Noise and the reality gap: The use of simulation in evolutionary robotics. In: Morán, F., Merelo, J.J., Moreno, A., Chacon, P. (eds.) ECAL 1995. LNCS, vol. 929, pp. 704–720. Springer, Heidelberg (1995)

    Google Scholar 

  6. Sims, K.: Evolving virtual creatures. In: Proceedings of the 21st annual conference on Computer graphics and interactive techniques, pp. 15–22. ACM Press, New York (1994)

    Chapter  Google Scholar 

  7. Hornby, G.S.: Generative Representations for Evolutionary Design Automation. PhD thesis, Brandeis University, Dept. of Computer Science, Boston, MA, USA (2003)

    Google Scholar 

  8. Hornby, G.S., Pollack, J.B.: The advantages of generative grammatical encodings for physical design. In: Proceedings of the 2001 Congress on Evolutionary Computation CEC 2001, COEX, World Trade Center, 159 Samseong-dong, Gangnam-gu, Seoul, Korea, pp. 600–607. IEEE Press, Los Alamitos (2001)

    Chapter  Google Scholar 

  9. Toussaint, M.: Demonstrating the evolution of complex genetic representations: An evolution of artificial plants. 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, Springer, Heidelberg (2003)

    Google Scholar 

  10. Bongard, J.C., Pfeifer, R.: Repeated structure and dissociation of genotypic and phenotypic complexity in artificial ontogeny. In: Spector, L., Goodman, E.D., Wu, A., Langdon, W.B., Voigt, H.M., Gen, M., Sen, S., Dorigo, M., Pezeshk, S., Garzon, M.H., Burke, E. (eds.) Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2001), San Francisco, California, USA, pp. 829–836. Morgan Kaufmann, San Francisco (2001)

    Google Scholar 

  11. Funes, P.: Evolution of Complexity in Real-World Domains. PhD thesis, Brandeis University, Dept. of Computer Science, Boston, MA, USA (2001)

    Google Scholar 

  12. Koza, J.R.: Genetic Programming: on the Programming of Computers by Means of Natural Selection. MIT Press, Cambridge (1992)

    MATH  Google Scholar 

  13. Viswanathan, S., Pollack, J.: On the evolvability of replication fidelity in stochastic construction. Technical Report CS-04-248, Brandeis University (2003)

    Google Scholar 

  14. Coello, C.A.C.: An updated survey of evolutionary multiobjective optimization techniques: State of the art and future trends. In: Angeline, P.J., Michalewicz, Z., Schoenauer, M., Yao, X., Zalzala, A. (eds.) Proceedings of the Congress on Evolutionary Computation, Mayflower Hotel, Washington D.C., USA, vol. 1, pp. 3–13. IEEE Press, Los Alamitos (1999)

    Google Scholar 

  15. Fonseca, C.M., Fleming, P.J.: Genetic algorithms for multiobjective optimization: Formulation, discussion and generalization. In: Genetic Algorithms: Proceedings of the Fifth International Conference, pp. 416–423. Morgan Kaufmann, San Francisco (1993)

    Google Scholar 

  16. Winston, H.P.: Learning By Analyzing Differences. In: Artificial Intelligence, 3rd edn., pp. 349–364. Addison-Wesley, Reading (1993)

    Google Scholar 

  17. De Jong, E.D., Watson, R.A., Pollack, J.B.: Reducing bloat and promoting diversity using multi-objective methods. In: Spector, L., Goodman, E., Wu, A., Langdon, W., Voigt, H.M., Gen, M., Sen, S., Dorigo, M., Pezeshk, S., Garzon, M., Burke, E. (eds.) Proceedings of the Genetic and Evolutionary Computation Conference, GECCO-2001, San Francisco, CA, pp. 11–18. Morgan Kaufmann Publishers, San Francisco (2001)

    Google Scholar 

  18. Langdon, W.B.: The evolution of size in variable length representations. In: 1998 IEEE International Conference on Evolutionary Computation, Anchorage, Alaska, USA, pp. 633–638. IEEE Press, Los Alamitos (1998)

    Google Scholar 

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

Rieffel, J., Pollack, J. (2004). The Emergence of Ontogenic Scaffolding in a Stochastic Development Environment. 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_83

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-24854-5_83

  • 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

pFad - Phonifier reborn

Pfad - The Proxy pFad of © 2024 Garber Painting. All rights reserved.

Note: This service is not intended for secure transactions such as banking, social media, email, or purchasing. Use at your own risk. We assume no liability whatsoever for broken pages.


Alternative Proxies:

Alternative Proxy

pFad Proxy

pFad v3 Proxy

pFad v4 Proxy