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International Conference on Evolutionary and Biologically Inspired Music and Art

EvoMUSART 2015: Evolutionary and Biologically Inspired Music, Sound, Art and Design pp 78–88Cite as

Avoidance Drawings Evolved Using Virtual Drawing Robots

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9027))

Abstract

We introduce a generative system for “avoidance drawings”, drawings made by virtual drawing robots executing a random walk while simultaneously avoiding the paths of other robots. The random walk method is unique and is based on a curvature controlling scheme initially introduced by Chappell. We design a fitness function for evaluating avoidance drawings and an evolutionary framework for evolving them. This requires us to follow principles we elucidate for simulated evolution where the generative system is highly stochastic in nature. Examples document the evolutionary system’s efficacy and success.

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Author information

Authors and Affiliations

  1. University of Richmond, Richmond, VA, 23173, USA

    Gary Greenfield

Authors
  1. Gary Greenfield
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Corresponding author

Correspondence to Gary Greenfield .

Editor information

Editors and Affiliations

  1. University of Kent, Canterbury, United Kingdom

    Colin Johnson

  2. University of A Coruña, A Coruña, Spain

    Adrian Carballal

  3. University of Coimbra, Coimbra, Portugal

    João Correia

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Greenfield, G. (2015). Avoidance Drawings Evolved Using Virtual Drawing Robots. In: Johnson, C., Carballal, A., Correia, J. (eds) Evolutionary and Biologically Inspired Music, Sound, Art and Design. EvoMUSART 2015. Lecture Notes in Computer Science(), vol 9027. Springer, Cham. https://doi.org/10.1007/978-3-319-16498-4_8

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  • DOI: https://doi.org/10.1007/978-3-319-16498-4_8

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-16497-7

  • Online ISBN: 978-3-319-16498-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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