Eelco den Heijer

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In this paper we investigate and compare four aesthetic measures within the context of evolutionary art. We evolve visual art with an unsupervised evolutionary art system using genetic programming and an aesthetic measure as the fitness function. We perform multiple experiments with different aesthetic measures and examine their influence on the evolved(More)
In this paper we investigate the applicability of Multi-Objective Optimization (MOO) in Evolutionary Art. We evolve images using an unsupervised evolutionary algorithm and we use two aesthetic measures as fitness functions concurrently. We use three different pairs from a set of three aesthetic measures and we compare the output of each pair to the output(More)
We present an extensive study into aesthetic measures in unsupervised evolutionary art (EvoArt). In contrast to several mainstream EvoArt approaches we evolve images without human interaction, using one or more aesthetic measures as fitness functions. We perform a series of systematic experiments, comparing 7 di↵erent aesthetic measures through subjective(More)
In this paper we introduce the use of Scalable Vector Graphics (SVG) as a representation for 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 performed a number of(More)
In this paper we present our findings of our continued investigation into the use of Scalable Vector Graphics as a genotype representation in evolutionary art. In previous work we investigated the feasibility of SVG as a genetic representation for evolutionary art, and found that the representation was very flexible, but that the potential visual output was(More)