Abstract
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.
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References
Peitgen, H.O., Richter, P.H.: The Beauty of Fractals. Images of Complex Dynamical Systems. Springer, Heidelberg (1986)
Flake, G.W.: The Computational Beauty of Nature: Computer Explorations of Fractals, Chaos, Complex Systems, and Adaptation. MIT Press, Cambridge (2000)
Draves, S.: The electric sheep and their dreams in high fidelity, Annecy, France. ACM Press, New York (2006)
Peitgen, H.-O., Jürgens, H., Saupe, D.: Chaos and Fractals. Springer, Heidelberg (2004)
Draves, S.: Electric sheep, http://www.electricsheep.org
Dawkins, R.: The Blind Watchmaker. Penguin, London (1986)
Sims, K.: Artificial evolution for computer graphics. In: Proceedings of SIGGRAPH 1991. ACM Press, New York (1991)
Todd, S., Latham, W.: Evolutionary Art and Computers. Academic Press, London (1992)
Lutton, E., Cayla, E., Chapuis, J.: Artie-fract: The artist’s viewpoint. In: Evo Workshops [12], pp. 510–521
Engelbrecht, A.: Computational Intelligence: An Introduction. Halsted Press, New York (2002)
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)
An Evolutionary Modularized Data Mining Mechanism for Financial Distress Forecasts. Studies in Fuzziness and Soft Computing, vol. 163. Springer, Heidelberg (2006)
Khemka, N.: Comparing particle swarms and evolution strategies: Benchmarks and application, Master’s thesis, University of Calgary, Calgary, AB, Canada (2005)
Kramer, D., MacInnis, M.: Utilization of a local grid of mac os x-based computers using xgrid, hpdc, vol. 00, pp. 264–265 (2004)
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)
Pu, P., Punit, G.: Visualizing reputation and recommendation in scientific literature. In: 10th International Conference on Human - Computer Interaction, Crete, Greece (2003)
Jacob, C., Burleigh, I.: Biomolecular swarms - an agent-based model of the lactose operon. Natural Computing 3(4), 361–376 (2004)
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Moniz, R.D., Jacob, C. (2009). Fractal Evolver: Interactive Evolutionary Design of Fractals with Grid Computing. In: Giacobini, M., et al. Applications of Evolutionary Computing. EvoWorkshops 2009. Lecture Notes in Computer Science, vol 5484. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01129-0_50
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DOI: https://doi.org/10.1007/978-3-642-01129-0_50
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-01128-3
Online ISBN: 978-3-642-01129-0
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