- author = "Eelco {den Heijer} and A. E. Eiben",
- title = "Using aesthetic measures to evolve art",
- booktitle = "IEEE Congress on Evolutionary Computation (CEC 2010)",
- year = "2010",
- address = "Barcelona, Spain",
- month = "18-23 " # jul,
- publisher = "IEEE Press",
- keywords = "genetic algorithms, genetic programming",
- isbn13 = "978-1-4244-6910-9",
- size = "8 pages",
- abstract = "In this paper we investigate and compare three 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 images. Additionally, we perform a cross-evaluation by calculating the aesthetic value of images evolved by measure i according to measure j. This way we investigate the flexibility of each aesthetic measure (i.e., whether the aesthetic measure appreciates different types of images). Last, we perform an image analysis using a fixed set of image statistics functions. The results show that aesthetic measures have a rather clear 'style' and that these styles can be very different. Furthermore we find that some aesthetic measures show little flexibility and appreciate only a limited set of images. The images in this paper might only be in colour in the electronic version.",
-
DOI = "
doi:10.1109/CEC.2010.5586245",
-
notes = "Computational Aesthetics. Benford distribution,
Shannon entropy+Kolmogorov complexity. Arabitat (Art
Habitat) http://www.few.vu.nl/~eelco/(broken Apr 2019)
indexed colour table, 'an image that can be compressed
using PNG to 3percent or less of its original size is
discarded'. Table II - very little agreement between
different fitness measures.
WCCI 2010. Also known as \cite{5586245}",
