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Genetic and Evolutionary Computation Conference

GECCO 2004: Genetic and Evolutionary Computation – GECCO 2004 pp 1314–1315Cite as

Enhanced Innovation: A Fusion of Chance Discovery and Evolutionary Computation to Foster Creative Processes and Decision Making

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3103))

Abstract

Human-based genetic algorithms are powerful tools for organizational modeling. If we enhance them using chance discovery techniques, we obtain an innovative approach for computer-supported collaborative work. Moreover, such a user-centered approach fuses human and computer partners in a natural way. This paper presents a first test, as well as analyzes the obtained results, of real human and computer collaboration powered by the fusion of human-based genetics algorithms and chance discovery.

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References

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Author information

Authors and Affiliations

  1. Illinois Genetic Algorithms Laboratory (IlliGAL), National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign,  

    Xavier Llorà, Kei Ohnishi, Ying-ping Chen & David E. Goldberg

  2. Automated Learning Group, National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign,  

    Michael E. Welge

Authors
  1. Xavier Llorà
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  2. Kei Ohnishi
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  3. Ying-ping Chen
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  4. David E. Goldberg
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  5. Michael E. Welge
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Editor information

Editors and Affiliations

  1. Indian Institute of Technology Kanpur, Department of Mechanical Engineering, Kanpur Genetic Algorithms Laboratory (KanGAL), Kanpur, 208016, Uttar Pradesh, India

    Kalyanmoy Deb

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© 2004 Springer-Verlag Berlin Heidelberg

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Cite this paper

Llorà, X., Ohnishi, K., Chen, Yp., Goldberg, D.E., Welge, M.E. (2004). Enhanced Innovation: A Fusion of Chance Discovery and Evolutionary Computation to Foster Creative Processes and Decision Making. In: Deb, K. (eds) Genetic and Evolutionary Computation – GECCO 2004. GECCO 2004. Lecture Notes in Computer Science, vol 3103. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24855-2_143

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  • DOI: https://doi.org/10.1007/978-3-540-24855-2_143

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-22343-6

  • Online ISBN: 978-3-540-24855-2

  • eBook Packages: Springer Book Archive

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