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Probabilistic Decision Making for Interactive Evolution with Sensitivity Analysis

  • Conference paper
Evolutionary and Biologically Inspired Music, Sound, Art and Design (EvoMUSART 2014)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8601))

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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.

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Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, The Ohio State University, Columbus, OH, 43210, USA

    Jonathan Eisenmann & Rick Parent

  2. The Advanced Computing Center for the Arts and Design (ACCAD), The Ohio State University, Columbus, OH, 43210, USA

    Jonathan Eisenmann & Matthew Lewis

Authors
  1. Jonathan Eisenmann
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  2. Matthew Lewis
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  3. Rick Parent
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Editor information

Editors and Affiliations

  1. School of Computer Science, Department of Communications and Information Technologies, Campus de Elviña, University of A Coruña, 15071, A Coruña, Spain

    Juan Romero

  2. Complex and Adaptive Systems Laboratory, Lochlann Quinn School of Business, Donnybrook, University College Dublin, 4, Dublin, Ireland

    James McDermott

  3. CISUC, Department of Informatics Engineering, Pinhal de Marrocos, University of Coimbra, 3030, Coimbra, Portugal

    João Correia

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Eisenmann, J., Lewis, M., Parent, R. (2014). Probabilistic Decision Making for Interactive Evolution with Sensitivity Analysis. In: Romero, J., McDermott, J., Correia, J. (eds) Evolutionary and Biologically Inspired Music, Sound, Art and Design. EvoMUSART 2014. Lecture Notes in Computer Science, vol 8601. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-44335-4_1

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  • DOI: https://doi.org/10.1007/978-3-662-44335-4_1

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-44334-7

  • Online ISBN: 978-3-662-44335-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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