A Survey of Virtual Ecosystems in Generative Electronic Art

  • Alan Dorin
Part of the Natural Computing Series book series (NCS)


This paper explores the application of ecosystem simulation to the production of works of generative electronic art. The aim is to demonstrate that virtual ecosystems are capable of producing outcomes that are rich, complex and interesting aesthetically. A number of artworks that employ virtual ecosystems are surveyed. The author argues that the most interesting works of generative art exhibit four basic properties: coherence and unity; multi-scaled temporal complexity; autonomous production of novelty; responsiveness to perturbation. The virtual ecosystem is assessed for its suitability as a medium for constructing generative art in light of these desirable properties. It is concluded that the ecosystem’s strengths lie in its exhibition of multi-scaled complexity and its autonomous production of novelty. Whilst an artist may manipulate a simulation to retain visual and sonic coherence, the software also possesses an implicit coherence inherent in its ability to self-organize. Under some circumstances it appears that the weakness of the virtual ecosystem as an artistic medium lies in its unpredictable response to perturbation. Consequently, the paper also explores virtual ecosystems’ susceptibility to external control and describes methods that have been employed to adjust the responsiveness of art works that employ them.


Complex Adaptive System Generative Electronic Abiotic Environment Complexity Demonstrate Software Ecosystem 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Whitelaw, M. (2004). Metacreation: Art and Artificial Life. The MIT PressGoogle Scholar
  2. 2.
    Innocent, T. (1999). The language of iconica. In Dorin, A., McCormack, J., eds.: First Iteration, CEMA. MelbourneGoogle Scholar
  3. 3.
    McCormack, J. (2001). Eden: An evolutionary sonic ecosystem. In Kelemen, J., Sosìk, P., eds.: Advances in Artificial Life, 6th European Conference. Lecture Notes in Computer Science. Springer, 133–142Google Scholar
  4. 4.
    Tansley, A.G. (1935). The use and abuse of vegetational concepts and terms. Ecology, 16(3): 284–307CrossRefGoogle Scholar
  5. 5.
    Watson, A., Lovelock, J. (1983). Biological homeostasis of the global environment: The parable of daisyworld. Tellus B, 35: 284–289CrossRefGoogle Scholar
  6. 6.
    Yaeger, L. (1994). Computational genetics, physiology, metabolism, neural systems, learning, vision, and behavior or PolyWorld: Life in a new context. In Langton, C.G., ed.: Proceedings of the Workshop on Artificial Life (ALIFE ’92). Sante Fe Institute Studies in the Sciences of Complexity. Reading, MA, USA. Addison-Wesley, 263–298Google Scholar
  7. 7.
    Ray, T.S. (1992). An approach to the synthesis of life. In Langton, C.G., Tayler, C., Farmer, J.D., Rasmussen, S., eds.: Artificial Life II. Addison-Wesley. Reading, MA, 371–408Google Scholar
  8. 8.
    Burkhart, R., Askenazi, M., Minar, N. (2006). Swarm documentation set. http://www.santafe.edu/projects/swarm/swarmdocs/set/set.htmlGoogle Scholar
  9. 9.
    Holland, J.H. (1998). Hidden Order: How Adaptation Builds Complexity (Helix Books). Addison Wesley Publishing CompanyGoogle Scholar
  10. 10.
    Epstein, J.M., Axtell, R.L. (1996). Growing Artificial Societies: Social Science from the Bottom Up. Brookings InstituteGoogle Scholar
  11. 11.
    Adami, C., Brown, C.T. (1994). Evolutionary learning in the 2d artificial life system avida. In Brooks, R.A., Maes, P., eds.: Artificial Life IV: Proceedings of the Fourth International Workshop on the Synthesis and Simulation of Living Systems. Cambridge, MA, USA. MIT Press, 377–381Google Scholar
  12. 12.
    Deussen, O., Hanrahan, P., Lintermann, B., Mech, R., Pharr, M., Prusinkiewicz, P. (1998). Realistic modeling and rendering of plant ecosystems. In: SIGGRAPH ’98: Proceedings of the 25th Annual Conference on Computer Graphics and Interactive Techniques. New York, NY, USA. ACM Press, 275–286Google Scholar
  13. 13.
    Dorin, A. (2005). A co-evolutionary epidemiological model for artificial life and death. In Capcarrère, M.S., Freitas, A.A., Bentley, P.J., Johnson, C.G., Timmis, J., eds.: Advances in Artificial Life, 8th European Conference, ECAL. Lecture Notes in Computer Science. Springer, 775–784Google Scholar
  14. 14.
    Dahlstedt, P. (1999). Living melodies: Coevolution of sonic communication. In Dorin, A., McCormack, J., eds.: First Iteration, CEMA. Melbourne, 56–66Google Scholar
  15. 15.
    Berry, R., Rungsarityotin, W., Dorin, A., Dahlstedt, P., Haw, C. (2001). Unfinished symphonies – songs of 3.5 worlds. In: Workshop on Artificial Life Models for Musical Applications, Sixth European Conference on Artificial Life, Editoriale Bios. Prague, Czech Republic, 51–64Google Scholar
  16. 16.
    Sommerer, C., Mignonneau, L. (1999). VERBARIUM and LIFE SPACIES: Creating a visual language by transcoding text into form on the internet. In: VL ’99: Proceedings of the IEEE Symposium on Visual Languages. Washington, DC, USA. IEEE Computer Society, 90–95Google Scholar
  17. 17.
    Taylor, T. (2002). Creativity in evolution: individuals, interactions, and environments. In Bentley, P., Corne, D., eds.: Creative Evolutionary Systems. Morgan Kaufmann Publishers Inc.. San Francisco, CA, USA, 79–108Google Scholar
  18. 18.
    Dawkins, R. (1987). The Blind Watchmaker. W.W. Norton & Co. New YorkGoogle Scholar
  19. 19.
    Pargellis, A.N. (2000). Digital life behavior in the amoeba world. Artif. Life, 7(1): 63–75CrossRefGoogle Scholar
  20. 20.
    Todd, S., Latham, W. (1992). Evolutionary Art and Computers. Academic Press. San DiegoMATHGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Alan Dorin
    • 1
  1. 1.Centre for Electronic Media ArtFaculty of Information Technology, Monash UniversityClaytonAustralia 3800

Personalised recommendations