Skip to main content
SpringerLink
Log in
Book cover

International Conference on Unconventional Computing and Natural Computation

UCNC 2012: Unconventional Computation and Natural Computation pp 186–197Cite as

Genome Parameters as Information to Forecast Emergent Developmental Behaviors

  • Conference paper

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7445))

Abstract

In this paper we measure genomic properties in EvoDevo systems, to predict emergent phenotypic characteristic of artificial organisms. We describe and compare three parameters calculated out of the composition of the genome, to forecast the emergent behavior and structural properties of the developed organisms. The parameters are each calculated by including different genomic information. The genotypic information explored are: purely regulatory output, regulatory input and relative output considered independently and an overall parameter calculated out of genetic dependency properties. The goal of this work is to gain more knowledge on the relation between genotypes and the behavior of emergent phenotypes. Such knowledge will give information on genetic composition in relation to artificial developmental organisms, providing guidelines for construction of EvoDevo systems. A minimalistic developmental system based on Cellular Automata is chosen in the experimental work.

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   39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   49.99
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. Binder, P.M.: A Phase Diagram for Elementary Cellular Automata. Complex Systems 7, 241–247 (1993)

    Google Scholar 

  2. Binder, P.M.: Parametric Ordering of Complex Systems. Physical Review E 49(3), 2023–2025 (1994)

    Article  Google Scholar 

  3. De Oliveira, G., De Oliveira, P., Omar, N.: Guidelines for Dynamics-based Parametrization of One-Dimensional Cellular Automata Rule Space. Complexity 6(2) (2001)

    Google Scholar 

  4. De Oliveira, G., De Oliveira, P., Omar, N.: Definition and Application of a Five-Parameter Characterization of One-Dimensional Cellular Automata Rule Space. Artificial Life 7, 277–301 (2001)

    Article  Google Scholar 

  5. Li, W.: Phenomenology of Nonlocal Cellular Automata. Journal of Statistical Physics 68(5-6), 829–882 (1992)

    Article  MathSciNet  MATH  Google Scholar 

  6. Tufte, G., Nichele, S.: On the correlations between developmental diversity and genomic composition. In: GECCO 2011, pp. 1507–1514. ACM (2011)

    Google Scholar 

  7. Nichele, S., Tufte, G.: Trajectories and Attractors as Specification for the Evolution of Behavior in Cellular Automata. In: IEEE CEC 2010, pp. 4441–4448 (2010)

    Google Scholar 

  8. Beer, R.D.: A dynamical systems perspective on agent-environment interaction. Artificial Intelligence 72(1-2), 173–215 (1995)

    Article  Google Scholar 

  9. Bentley, P.J., Kumar, S.: Three ways to grow designs: A comparison of embryogenies for an evolutionary design problem. In: GECCO 1999, pp. 35–43 (1999)

    Google Scholar 

  10. Cussat-Blanc, S., Luga, H., Duthen, Y.: From single cell to simple creature morphology and metabolism. In: Bullock, S., Noble, J., Watson, R., Bedau, M.A. (eds.) Artificial Life XI, pp. 134–141. MIT Press, Cambridge (2008)

    Google Scholar 

  11. Eggenberger, P.: Evolving morphologies of simulated 3d organisms based on differential gene expression. In: 4th Artificial Life Conference, pp. 205–213. MIT Press (1997)

    Google Scholar 

  12. Fleischer, K., Barr, A.H.: A simulation testbed for the study of multicellular development: The multiple mechanisms of morphogenesis. In: 3rd Artificial Life Conference, pp. 389–416. Addison-Wesley (1993)

    Google Scholar 

  13. Forrest, S.: Emergent Computation. MIT Press (1991)

    Google Scholar 

  14. Gordon, T.G.W.: Exploring models of development for evolutionary circuit design. In: IEEE CEC 2003, pp. 2050–2057. IEEE (2003)

    Google Scholar 

  15. Hall, B.K., Pearson, R.D., Müller, G.B.: Environment, development, and Evolution Toward a Synthesis. The Vienna Series in Theoretical Biology. MIT-Press (2004)

    Google Scholar 

  16. Kitano, H.: Building Complex Systems Using Developmental Process: An Engineering Approach. In: Sipper, M., Mange, D., Pérez-Uribe, A. (eds.) ICES 1998. LNCS, vol. 1478, pp. 218–229. Springer, Heidelberg (1998)

    Chapter  Google Scholar 

  17. Kowaliw, T.: Measures of complexity for artificial embryogeny. In: GECCO 2008. ACM (2008)

    Google Scholar 

  18. Kowaliw, T., Grogono, P., Kharma, N.: Environment as a spatial constraint on the growth of structural form. In: GECCO 2007, New York, USA, pp. 1037–1044 (2007)

    Google Scholar 

  19. Kumar, S., Bentley, P.J.: Biologically Inspired Evolutionary Development. In: Tyrrell, A.M., Haddow, P.C., Torresen, J. (eds.) ICES 2003. LNCS, vol. 2606, pp. 57–68. Springer, Heidelberg (2003)

    Chapter  Google Scholar 

  20. Langton, C.G.: Self-reproduction in cellular automata. Physica D 10, 135–144 (1984)

    Article  Google Scholar 

  21. Langton, C.G.: Computation at the edge of chaos: phase transitions and emergent computation. In: Forrest, S. (ed.) Emergent Computation, pp. 12–37. MIT Press (1991)

    Google Scholar 

  22. Lehre, P.K., Haddow, P.C.: Developmental mappings and phenotypic complexity. In: Congress on Evolutionary Computation (CEC 2003), pp. 62–68. IEEE (2003)

    Google Scholar 

  23. Miller, J.F.: Evolving a Self-Repairing, Self-Regulating, French Flag Organism. In: Deb, K., Tari, Z. (eds.) GECCO 2004. LNCS, vol. 3102, pp. 129–139. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  24. Miller, J.F., Banzhaf, W.: Evolving the program for a cell: from french flag to boolean circuits. In: Kumar, S., Bentley, P.J. (eds.) On Growth, Form and Computers, pp. 278–301. Elsevier Limited, Oxford (2003)

    Chapter  Google Scholar 

  25. Mitchell, M., Hraber, P.T., Crutchfield, J.P.: Revisiting the egde of chaos: Evolving cellular automata to perform computations. Complex Systems 7, 89–130 (1993)

    MATH  Google Scholar 

  26. Packard, N.H.: Adaptation Toward the Edge of Chaos. In: Dynamic Patterns in Complex Systems, pp. 293–301. World Scientific (1988)

    Google Scholar 

  27. Tufte, G.: Evolution, development and environment toward adaptation through phenotypic plasticity and exploitation of external information. In: Bullock, S., Noble, J., Watson, R., Bedau, M.A. (eds.) Artificial Life XI, pp. 624–631. MIT Press, Cambridge (2008)

    Google Scholar 

  28. West-Eberhard, M.J.: Developmental Plasticity and Evolution. Oxford Univ. Press (2003)

    Google Scholar 

  29. Wolfram, S.: Universality and complexity in CA. Physica D 10(1-2), 1–35 (1984)

    Article  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Computer and Information Science, Norwegian University of Science and Technology, Sem Selandsvei 7-9, 7491, Trondheim, Norway

    Stefano Nichele & Gunnar Tufte

Authors
  1. Stefano Nichele
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Gunnar Tufte
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Laboratoire d’Informatique, Fondamentale d’Orléan et Départment d’informatique, UFR Sciences, Université d’Orléans, 45067, Orléans Cedex 2, France

    Jérôme Durand-Lose

  2. Department of Mathematics and Statistics, University of South Florida, 33620, Tampa, FL, USA

    Nataša Jonoska

Rights and permissions

Reprints and permissions

Copyright information

© 2012 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Nichele, S., Tufte, G. (2012). Genome Parameters as Information to Forecast Emergent Developmental Behaviors. In: Durand-Lose, J., Jonoska, N. (eds) Unconventional Computation and Natural Computation. UCNC 2012. Lecture Notes in Computer Science, vol 7445. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32894-7_18

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-32894-7_18

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-32893-0

  • Online ISBN: 978-3-642-32894-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation