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Embedding of Pixel-Based Evolutionary Algorithms in My Global Art Process

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Summary

My art comprises three levels: basic, methodical, and superordinate. The basic level refers to the production of individual works of art. At the methodical level, I am concerned with the development of artistic processes, in this case, inspired by evolutionary concepts. Finally, at the superordinate level, social sculpture, “Health Art”, is considered.

Between 1995 and 2003 I developed and used several pixel-based evolutionary art processes. These artistic approaches resort to biologically inspired concepts, such as population, variation, and selection. The individuals were pixel images. In the reproduction phase two (or more) individuals were selected as parents and the images were recombined by the exchange of image parts (Regions-of-Interest). Variation (mutation) was performed by means of image processing operations such as the rotation of image parts with random but constrained parameters. Parents and offspring were evaluated by the aesthetic preferences of the artist and the best individuals built the next generation.

A unique and more complex evolution art process was developed in 2004, with no direct correspondence to known evolutionary algorithms like GA, ES, or GP. It uses some additional evolutionary concepts, such as a global pool of images and multi-sexual recombination, together with ontogenetic concepts, such as spores or fruits, and other concepts such as image templates. In a narrow sense, there is no change of generations of image individuals. Selected individuals are directly inserted into the global image pool, being also involved in a second reproduction process where they are transformed by mathematical symmetry operations. The resulting images are also inserted into the global image pool, while all the images in this pool build the basis for recombination in the next generation.

Future plans, about file formats, other image reproduction operators, image databases, and aesthetic preference modelling, are also discussed.

Keywords

  • Image Individual
  • Bilateral Symmetry
  • Absorber Material
  • Plane Group
  • Image Part

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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Bachelier, G. (2008). Embedding of Pixel-Based Evolutionary Algorithms in My Global Art Process. 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_12

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  • DOI: https://doi.org/10.1007/978-3-540-72877-1_12

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