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Solution Space Visualization

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Machine Learning for Evolution Strategies

Part of the book series: Studies in Big Data ((SBD,volume 20))

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Abstract

Visualization is the discipline of analyzing and designing algorithms for visual representations of information to reinforce human cognition. It covers many scientific fields like computational geometry or data analysis and finds numerous applications. Examples reach from biomedical visualization and cyber-security to geographic visualization, and multivariate time series visualization. For understanding of optimization processes in high-dimensional solution spaces, visualization offers useful tools for the practitioner.

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Authors and Affiliations

  1. Informatik, Universität Oldenburg, Oldenburg, Germany

    Oliver Kramer

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  1. Oliver Kramer
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Correspondence to Oliver Kramer .

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© 2016 Springer International Publishing Switzerland

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Kramer, O. (2016). Solution Space Visualization. In: Machine Learning for Evolution Strategies. Studies in Big Data, vol 20. Springer, Cham. https://doi.org/10.1007/978-3-319-33383-0_9

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  • DOI: https://doi.org/10.1007/978-3-319-33383-0_9

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-33381-6

  • Online ISBN: 978-3-319-33383-0

  • eBook Packages: EngineeringEngineering (R0)

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