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Chance Discovery pp 276–301Cite as

Discovering Deep Building Blocks for Competent Genetic Algorithms Using Chance Discovery via KeyGraphs

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Part of the book series: Advanced Information Processing ((AIP))

Summary

In this chapter, we see whether chance discovery in the form of KeyGraphs can be used to reveal deep building blocks for competent genetic algorithms(GAs), thereby speeding up innovation in particularly difficult problems. On an intellectual level, showing the connection between KeyGraphs and genetic algorithms as related pieces of the innovation puzzle is both scientifically and computationally interesting. GAs represent that aspect of human innovation that tries to innovate through the exchange or cross fertilization of notions contained in different ideas; the KeyGraph procedure represents that portion of human innovation that pays special attention to and interprets salient fortuitous events. The chapter goes beyond mere conjecture and performs pilot studies that show how KeyGraphs and competent GAs can work together to solve the problem of deep building blocks; the work is promising and steps toward a practical computational combination of the two procedures are suggested.

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Author information

Authors and Affiliations

  1. Illinois Genetic Algorithms Laboratory (IlliGAL), Department of General Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, 61 801, USA

    David E. Goldberg & Kumara Sastry

  2. The Laboratory of Chance Discovery, Graduate School of Business Sciences, University of Tsukuba, Otsuka, Tokyo, Japan

    Yukio Ohsawa

Authors
  1. David E. Goldberg
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  2. Kumara Sastry
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  3. Yukio Ohsawa
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Editor information

Editors and Affiliations

  1. Graduate School of Business Sciences, University of Tsukuba, GSSM, University of Tsukuba, 3-29-1 Otsuka, 112-0012, Bunkyo-ku, Tokyo, Japan

    Yukio Ohsawa

  2. Agent Applications, Research and Technology (Agent ART) Group, Department of Computer Science, University of Liverpool, L69 7ZF, Liverpool, UK

    Peter McBurney

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© 2003 Springer-Verlag Berlin Heidelberg

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Goldberg, D.E., Sastry, K., Ohsawa, Y. (2003). Discovering Deep Building Blocks for Competent Genetic Algorithms Using Chance Discovery via KeyGraphs . In: Ohsawa, Y., McBurney, P. (eds) Chance Discovery. Advanced Information Processing. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-06230-2_19

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  • DOI: https://doi.org/10.1007/978-3-662-06230-2_19

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-05609-3

  • Online ISBN: 978-3-662-06230-2

  • eBook Packages: Springer Book Archive

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