Using scalable vector graphics to evolve art

In this paper we describe our investigations of the use of Scalable Vector Graphics as a genotype representation in evolutionary art. We describe the technical aspects of using SVG in evolutionary art, and explain the genetic operators mutation and crossover. Furthermore, we compare the use of SVG with existing representations in evolutionary art. We perform two series of experiments and describe their setup and results. In the first series of experiments we investigate the feasibility of SVG as a genotype representation for evolutionary art, and we evolve abstract images using a number of aesthetic measures as fitness functions (all experiments described in this paper are done without a human in the loop). We found that SVG is suitable as a genotype representation for evolutionary art, but that the range of the visual output was limited by the design of our genetic operators. In order to increase the range of the visual output, and in order to evolve representational images, we performed a second series of experiments in which we used existing images as source material. We designed and implemented a new initialisation, crossover and mutation operator. We also designed and implemented an ad-hoc aesthetic measure for ‘pop-art’ and used this to evolve images that are visually similar to screen printing art and pop art. All images and SVG code examples in this paper are available at http://www.few.vu.nl/~eelco