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Evolutionary Computation: Centralized, Parallel or Collaborative

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Computational Intelligence

Part of the book series: Intelligent Systems Reference Library ((ISRL,volume 1))

Abstract

This chapter discusses the nature and the importance of spatial interactions in evolutionary computation. The current state of evolution theories is discussed. An interaction model is investigated which we have called Darwin’s continent-island cycle conjecture. Darwin argued that such a cycle is the most efficient for successful evolution. This bold conjecture has not yet been noticed in science. We confirm Darwin’s conjecture using an evolutionary game based on the iterated prisoner’s dilemma. A different interaction scheme, called the stepping-stone model is used by the Parallel Genetic Algorithm PGA. The PGA is used to solve combinatorial optimization problems. Then the Breeder Genetic Algorithm BGA used for global optimization of continuous functions is described. The BGA uses competition between subpopulations applying different strategies. This kind of interaction is found in ecological systems.

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Author information

Authors and Affiliations

  1. Fraunhofer Institut Autonomous intelligent Systems Schloss Birlinghoven, 53757, Sankt Augustin, Germany

    Heinz Mühlenbein

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  1. Heinz Mühlenbein
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Editors and Affiliations

  1. School of Computer Science, Cardiff University , 5 The Parade,Roath, CF24 3AA, Cardiff, UK

    Christine L. Mumford

  2. University of South Australia Adelaide , Mawson Lakes Campus, South Australia, Australia

    Lakhmi C. Jain

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Mühlenbein, H. (2009). Evolutionary Computation: Centralized, Parallel or Collaborative. In: Mumford, C.L., Jain, L.C. (eds) Computational Intelligence. Intelligent Systems Reference Library, vol 1. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01799-5_17

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  • DOI: https://doi.org/10.1007/978-3-642-01799-5_17

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-01798-8

  • Online ISBN: 978-3-642-01799-5

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