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Proceedings Paper

Results on a fractal measure for evolutionary optimization
Author(s): Peter J. Angeline
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Paper Abstract

Evolutionary optimizers employ independent Gaussian random variables as a central component for their processing, which often renders them immune to analysis. This paper investigates the applicability of the Hurst dimension, a fractal dimension, as a characterization of processing in an evolutionary optimizer. Results show that this fractal measure does highlight some interesting processing commonalities between standard and self-adaptive evolutionary optimization. A potentially worthwhile modification to evolutionary optimization is suggested based on the results.

Paper Details

Date Published: 11 March 2002
PDF: 8 pages
Proc. SPIE 4739, Applications and Science of Computational Intelligence V, (11 March 2002); doi: 10.1117/12.458701
Show Author Affiliations
Peter J. Angeline, Natural Selection, Inc. (United States)


Published in SPIE Proceedings Vol. 4739:
Applications and Science of Computational Intelligence V
Kevin L. Priddy; Paul E. Keller; Peter J. Angeline, Editor(s)

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