Probabilistic Decision Making for Interactive Evolution with Sensitivity Analysis

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Jonathan Eisenmann, Matthew Lewis, Rick Parent: Probabilistic Decision Making for Interactive Evolution with Sensitivity Analysis. In: EvoMUSART 2014, S. 1-12.

DOI

http://link.springer.com/10.1007/978-3-662-44335-4_1

Abstract

Recent research in the area of evolutionary algorithms and interactive design tools for ideation has investigated how sensitivity analysis can be used to enable region-of-interest selection on design candidates. Even though it provides more precise control over the evolutionary search to the designer, the existing methodology for this enhancement to evolutionary algorithms does not make full use of the information provided by sensitivity analysis and may lead to premature convergence. In this paper, we describe the shortcomings of previous research on this topic and introduce an approach that mitigates the problem of early convergence. A discussion of the trade-offs of different approaches to sensitivity analysis is provided as well as a demonstration of this new technique on a parametric model built for character design ideation.

Extended Abstract

Bibtex

@incollection{
year={2014},
isbn={978-3-662-44334-7},
booktitle={Evolutionary and Biologically Inspired Music, Sound, Art and Design},
volume={8601},
series={Lecture Notes in Computer Science},
editor={Romero, Juan and McDermott, James and Correia, João},
doi={10.1007/978-3-662-44335-4_1},
title={Probabilistic Decision Making for Interactive Evolution with Sensitivity Analysis},
url={http://dx.doi.org/10.1007/978-3-662-44335-4_1 http://de.evo-art.org/index.php?title=Probabilistic_Decision_Making_for_Interactive_Evolution_with_Sensitivity_Analysis },
publisher={Springer Berlin Heidelberg},
keywords={interactive evolution; sensitivity analysis; probabilistic genetic operators},
author={Eisenmann, Jonathan and Lewis, Matthew and Parent, Rick},
pages={1-12},
language={English}
}

Used References

Dawkins, R.: The Blind Watchmaker: Why the Evidence of Evolution Reveals a Universe Without Design. Norton (1986), http://books.google.com/books?id=sPpaZnZMDG0C

Herman, J.D.: SALib (October 2013), https://github.com/jdherman/SALib

Herman, J.D., Kollat, J.B., Reed, P.M., Wagener, T.: Technical note: Method of Morris effectively reduces the computational demands of global sensitivity analysis for distributed watershed models. Hydrology and Earth System Sciences Discussions 10(4), 4275–4299 (2013), http://dx.doi.org/10.5194/hessd-10-4275-2013

Joe, S., Kuo, F.Y.: Constructing Sobol Sequences with Better Two-Dimensional Projections. SIAM J. Sci. Comput. 30(5), 2635–2654 (2008), http://dx.doi.org/10.1137/070709359

Kim, V.G., Li, W., Mitra, N.J., DiVerdi, S., Funkhouser, T.: Exploring collections of 3D models using fuzzy correspondences. ACM Trans. Graph. 31(4) (July 2012), http://dx.doi.org/10.1145/2185520.2185550

Morris, M.D.: Factorial Sampling Plans for Preliminary Computational Experiments. Technometrics 33(2), 161–174 (1991), http://dx.doi.org/10.2307/1269043

Perlin, K.: Improving noise. ACM Trans. Graph. 21(3), 681–682 (2002), http://dx.doi.org/10.1145/566570.566636

Saltelli, A., Chan, K.: Scott: Sensitivity analysis. J. Wiley & Sons. (2000), http://www.worldcat.org/isbn/0470743824

Shan, S., Wang, G.G.: Survey of modeling and optimization strategies to solve high-dimensional design problems with computationally-expensive black-box functions. Structural and Multidisciplinary Optimization 41(2), 219–241 (2010), http://dx.doi.org/10.1007/s00158-009-0420-2

Side Effects Software: HOUDINI FX. HOUDINI (2013), http://www.sidefx.com

Sobol, I.M.: Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates. Mathematics and Computers in Simulation 55(1-3), 271–280 (2001), http://dx.doi.org/10.1016/s0378-47540000270-6

Takagi, H., Kishi, K.: On-line knowledge embedding for an interactive EC-based montage system, pp. 280–283 (December 1999), http://dx.doi.org/10.1109/kes.1999.820178

Takagi, H.: New IEC Research and Frameworks Aspects of Soft Computing, Intelligent Robotics and Control. In: Fodor, J., Kacprzyk, J. (eds.) Aspects of Soft Computing, Intelligent Robotics and Control. SCI, vol. 241, pp. 65–76. Springer, Heidelberg (2009), http://dx.doi.org/10.1007/978-3-642-03633-0_4

- Stephen Todd, William Latham: Evolutionary Art and Computers. 1 Aufl., Academic Press Inc, Orlando, 1992, ISBN 978-0124371859, 288 Seiten. http://www.worldcat.org/isbn/9780124371859

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