An Indirect Fitness Scheme for Automated Evolution of Aesthetic Images

  • Gary Greenfield
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8601)


Recently, the question of whether artifacts obtained from a generative art system can be judged as creative based on the characteristics of their offspring has received considerable attention. Here, we focus on the question of whether aesthetic images can be evolved by considering characteristics of their offspring. We introduce a formal model for designing fitness functions for use in automated evolution of aesthetic images whereby genotypes are evaluated relative to certain characteristics of their offspring. We describe the results of an experiment using such an indirect fitness scheme that promotes offspring diversity in order to help select for parent phenotypes with desired symmetry and complexity properties. We use as our image generation platform a variant of the Sims’ classical Evolving Expressions generative art system.


Expression Tree Interactive Evolution Parent Phenotype Aesthetic Evaluation Interactive Evolutionary Computation 
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 2014

Authors and Affiliations

  • Gary Greenfield
    • 1
  1. 1.University of RichmondRichmondUSA

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