Fractal Evolver: Interactive Evolutionary Design of Fractals with Grid Computing

  • Ryan D. Moniz
  • Christian Jacob
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5484)


Interactive Evolutionary Computing is a powerful methodology that can be incorporated into the creative design process. However, for such a system to be useful, the evolutionary process should be simple to understand and easy to operate. This is especially true in applications where it is difficult to create a mathematical formula or model of the fitness evaluation, or where the quality of the solution is subjective and dependent on aesthetics, such as in the areas of art and music. Our paper explores this idea further by presenting a system that evolves fractal patterns using an interactive evolutionary design process. The result is a tool, Fractal Evolver, that employs grid computing and swarm intelligence concepts through particle swarm optimization to evolve fractal designs.


Interactive Evolution Distributed Parallel Interface Particle Swarm Optimization Fractals 


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  1. 1.
    Peitgen, H.O., Richter, P.H.: The Beauty of Fractals. Images of Complex Dynamical Systems. Springer, Heidelberg (1986)zbMATHGoogle Scholar
  2. 2.
    Flake, G.W.: The Computational Beauty of Nature: Computer Explorations of Fractals, Chaos, Complex Systems, and Adaptation. MIT Press, Cambridge (2000)zbMATHGoogle Scholar
  3. 3.
    Draves, S.: The electric sheep and their dreams in high fidelity, Annecy, France. ACM Press, New York (2006)CrossRefGoogle Scholar
  4. 4.
    Peitgen, H.-O., Jürgens, H., Saupe, D.: Chaos and Fractals. Springer, Heidelberg (2004)CrossRefzbMATHGoogle Scholar
  5. 5.
    Draves, S.: Electric sheep,
  6. 6.
    Dawkins, R.: The Blind Watchmaker. Penguin, London (1986)Google Scholar
  7. 7.
    Sims, K.: Artificial evolution for computer graphics. In: Proceedings of SIGGRAPH 1991. ACM Press, New York (1991)Google Scholar
  8. 8.
    Todd, S., Latham, W.: Evolutionary Art and Computers. Academic Press, London (1992)zbMATHGoogle Scholar
  9. 9.
    Lutton, E., Cayla, E., Chapuis, J.: Artie-fract: The artist’s viewpoint. In: Evo Workshops [12], pp. 510–521Google Scholar
  10. 10.
    Engelbrecht, A.: Computational Intelligence: An Introduction. Halsted Press, New York (2002)Google Scholar
  11. 11.
    Eberhart, R.C., Kennedy, J.: A new optimizer using particles swarm theory. In: Proc. Sixth International Symposium on Micro Machine and Human Science, Nagoya, Japan, pp. 39–43. IEEE Service Center, Piscataway (1995)CrossRefGoogle Scholar
  12. 12.
    An Evolutionary Modularized Data Mining Mechanism for Financial Distress Forecasts. Studies in Fuzziness and Soft Computing, vol. 163. Springer, Heidelberg (2006)Google Scholar
  13. 13.
    Khemka, N.: Comparing particle swarms and evolution strategies: Benchmarks and application, Master’s thesis, University of Calgary, Calgary, AB, Canada (2005)Google Scholar
  14. 14.
    Kramer, D., MacInnis, M.: Utilization of a local grid of mac os x-based computers using xgrid, hpdc, vol. 00, pp. 264–265 (2004)Google Scholar
  15. 15.
    Kamalian, R., Zhang, Y., Takagi, H., Agogino, A.M.: Reduced human fatigue interactive evolutionary computation for micromachine design. In: Proceedings of 2005 International Conference on Machine Learning and Cybernetics, vol. 9, pp. 5666–5671 (August 2005)Google Scholar
  16. 16.
    Pu, P., Punit, G.: Visualizing reputation and recommendation in scientific literature. In: 10th International Conference on Human - Computer Interaction, Crete, Greece (2003)Google Scholar
  17. 17.
    Jacob, C., Burleigh, I.: Biomolecular swarms - an agent-based model of the lactose operon. Natural Computing 3(4), 361–376 (2004)MathSciNetCrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Ryan D. Moniz
    • 1
  • Christian Jacob
    • 1
  1. 1.Computer ScienceUniversity of CalgaryCalgaryCanada

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