Manipulating Artificial Ecosystems

  • Alice Eldridge
  • Alan Dorin
  • Jon McCormack
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4974)


Artificial ecosystems extend traditional evolutionary approaches in generative art in several unique and attractive ways. However some of these traits also make them difficult to work with in a creative context. This paper addresses the issue by adapting predictive modelling tools from theoretical ecology. Inspired by the ecological concept of specialism, we construct a parameterised fitness curve that controls the relative efficacy of generalist and specialist strategies. We use this to influence the population’s trajectory through phenotype space. We also demonstrate the influence of environmental structure in biasing evolutionary outcomes. These ideas are applied in a creative ecosystem, ColourCycling which generates abstract images.


Patch Size Environmental Structure Resource Type Theoretical Ecology Resource Preference 
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.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Alice Eldridge
    • 1
  • Alan Dorin
    • 1
  • Jon McCormack
    • 1
  1. 1.Centre for Electronic Media ArtMonash UniversityAustralia

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