Comparing Aesthetic Measures for Evolutionary Art

  • E. den Heijer
  • A. E. Eiben
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6025)


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 images. To this end we store the 5 fittest individuals of each run and hand-pick the best 9 images after finishing the whole series. This way we create a portfolio of evolved art for each aesthetic measure for visual inspection. 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 flexiblity of each aesthetic measure (i.e., whether the aesthetic measure appreciates different types of images). 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 very little flexibility and appreciate only a limited set of images.


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  1. 1.
    Bentley, P.J., Corne, D.W. (eds.): Creative Evolutionary Systems. Morgan Kaufmann, San Mateo (2001)Google Scholar
  2. 2.
    Birkhoff, G.D.: Aesthetic Measure. Harvard University Press, Cambridge (1933)zbMATHGoogle Scholar
  3. 3.
    Deb, K.: Multi-objective Optimization using Evolutionary Algorithms. Wiley, Chichester (2001)zbMATHGoogle Scholar
  4. 4.
    Greenfield, G.: On the origins of the term “computational aesthetics”. In: Neumann, et al. (eds.) [10], pp. 9–12Google Scholar
  5. 5.
    Hoenig, F.: Defining computational aesthetics. In: Neumann, et al. (eds.) [10], pp. 13–18Google Scholar
  6. 6.
    Klinger, A., Salingaros, N.A.: A pattern measure. Environment and Planning B: Planning and Design 27, 537–547 (2000)CrossRefGoogle Scholar
  7. 7.
    Koza, J.R.: Genetic Programming: On the Programming of Computers by Means of Natural Selection. MIT Press, Cambridge (1992)zbMATHGoogle Scholar
  8. 8.
    Machado, P., Cardoso, A.: Computing aesthetics. In: de Oliveira, F.M. (ed.) SBIA 1998. LNCS (LNAI), vol. 1515, pp. 219–228. Springer, Heidelberg (1998)Google Scholar
  9. 9.
    Machado, P., Cardoso, A.: All the truth about nevar. Applied Intelligence 16(2), 101–118 (2002)zbMATHCrossRefGoogle Scholar
  10. 10.
    Neumann, L., Sbert, M., Gooch, B., Purgathofer, W. (eds.): Computational Aesthetics 2005: Eurographics Workshop on Computational Aesthetics in Graphics, Visualization and Imaging 2005, Girona, Spain, May 18-20. Eurographics Association (2005)Google Scholar
  11. 11.
    Rigau, J., Feixas, M., Sbert, M.: Informational aesthetics measures. IEEE Computer Graphics and Applications 28(2), 24–34 (2008)CrossRefGoogle Scholar
  12. 12.
    Romero, J., Machado, P. (eds.): The Art of Artificial Evolution: A Handbook on Evolutionary Art and Music. Natural Computing Series. Springer, Heidelberg (2007)Google Scholar
  13. 13.
    Rooke, S.: Eons of genetically evolved algorithmic images. In: Bentley and Corne [1], pp. 339–365Google Scholar
  14. 14.
    Ross, B., Ralph, W., Zong, H.: Evolutionary image synthesis using a model of aesthetics. In: IEEE Congress on Evolutionary Computation, CEC 2006, pp. 1087–1094 (2006)Google Scholar
  15. 15.
    Sims, K.: Artificial evolution for computer graphics. In: SIGGRAPH 1991: Proceedings of the 18th annual conference on Computer graphics and interactive techniques, vol. 25, pp. 319–328. ACM Press, New York (1991)CrossRefGoogle Scholar
  16. 16.
    Spehar, B., Clifford, C.W.G., Newell, B.R., Taylor, R.P.: Universal aesthetic of fractals. Computers & Graphics 27(5), 813–820 (2003)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • E. den Heijer
    • 1
    • 2
  • A. E. Eiben
    • 2
  1. 1.Objectivation B.V.AmsterdamThe Netherlands
  2. 2.Vrije UniversiteitAmsterdamThe Netherlands

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