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Co-evolutionary Methods in Evolutionary Art

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Summary

Following the ground breaking work of Sims and Latham there was a flurry of activity in interactive artificial evolution of images. However, the move towards non-interactive evolution of images that arises by invoking fitness functions to serve in place of users in order to guide simulated evolution proceeded haltingly and unevenly. If evolutionary computational models for image evolution are indeed inspired by nature, then it is natural to consider image evolution in the broader co-evolutionary context. This chapter briefly surveys the role co-evolutionary methods have played in evolutionary computation and then examines some of the instances where it has been applied to evolutionary art. The paucity of examples leads to a discussion of the challenges faced, and the difficulties encountered, when trying to use co-evolutionary methods both in evolutionary art and artificial creativity.

Keywords

  • Host Image
  • Image Evolution
  • Image Population
  • Sorting Network
  • Network Genotype

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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Greenfield, G.R. (2008). Co-evolutionary Methods in Evolutionary Art. In: Romero, J., Machado, P. (eds) The Art of Artificial Evolution. Natural Computing Series. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72877-1_17

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  • DOI: https://doi.org/10.1007/978-3-540-72877-1_17

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