Fractal Evolver: Interactive Evolutionary Design of Fractals with Grid Computing
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.
KeywordsInteractive Evolution Distributed Parallel Interface Particle Swarm Optimization Fractals
Unable to display preview. Download preview PDF.
- 5.Draves, S.: Electric sheep, http://www.electricsheep.org
- 6.Dawkins, R.: The Blind Watchmaker. Penguin, London (1986)Google Scholar
- 7.Sims, K.: Artificial evolution for computer graphics. In: Proceedings of SIGGRAPH 1991. ACM Press, New York (1991)Google Scholar
- 9.Lutton, E., Cayla, E., Chapuis, J.: Artie-fract: The artist’s viewpoint. In: Evo Workshops , pp. 510–521Google Scholar
- 10.Engelbrecht, A.: Computational Intelligence: An Introduction. Halsted Press, New York (2002)Google Scholar
- 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.Khemka, N.: Comparing particle swarms and evolution strategies: Benchmarks and application, Master’s thesis, University of Calgary, Calgary, AB, Canada (2005)Google Scholar
- 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.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.Pu, P., Punit, G.: Visualizing reputation and recommendation in scientific literature. In: 10th International Conference on Human - Computer Interaction, Crete, Greece (2003)Google Scholar