Using scalable vector graphics to evolve art

Created by W.Langdon from gp-bibliography.bib Revision:1.7630

@Article{DenHeijer:2016:IJART,

• title = "Using scalable vector graphics to evolve art",
• author = "Eelco {Den Heijer} and A. E. Eiben",
• journal = "Int. J. of Arts and Technology",
• year = "2016",
• month = mar # "~22",
• volume = "9",
• number = "1",
• pages = "59--85",
• keywords = "genetic algorithms, genetic programming, evolutionary computation, evolutionary art, scalable vector graphics, SVG, initialisation, genotype representation, abstract images, aesthetics, fitness functions",
• publisher = "Inderscience Publishers",
• ISSN = "1754-8861",
• bibsource = "OAI-PMH server at www.inderscience.com",
• language = "eng",
• URL = "http://www.inderscience.com/link.php?id=75408",
• DOI = "doi:10.1504/IJART.2016.075408",
• size = "27 pages",
• abstract = "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 our custom, SVG specific operators initialisation, mutation and crossover. We perform two series of experiments; in the first series of experiments, we investigate the feasibility of SVG as a genotype representation for evolutionary art, and evolve abstract images using a number of aesthetic measures as fitness functions. In the second series of experiments, we used existing images as source material. We also designed and implemented an ad-hoc aesthetic measure for pop-art and used this to evolve images that are visually similar to pop-art. All experiments described in this paper are done without a human in the loop. All images and SVG code examples in this paper are available at http://www.eelcodenheijer.nl/research.",

}

Genetic Programming entries for Eelco den Heijer Gusz Eiben

Citations