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Dual Phase Evolution as a Framework for Understanding Complex Adaptive Systems

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Computational Intelligence (IJCCI 2009)

Part of the book series: Studies in Computational Intelligence ((SCI,volume 343))

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Abstract

Evidence from several fields suggests that dual phase evolution (DPE) may contribute to distinctive features associated with complex adaptive systems. Here, we review empirical and theoretical evidence for DPE in natural systems and discuss the relationship of DPE to self-organised criticality and adaptive cycles. We describe a general model for DPE in networks, and present preliminary data illustrating the emergence of phase changes.

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Authors and Affiliations

  1. Clayton School of Information Technology, Monash University, Vic. 3800, Australia

    Greg Paperin & Suzanne Sadedin

Authors
  1. Greg Paperin
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  2. Suzanne Sadedin
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Corresponding author

Correspondence to Greg Paperin .

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Editors and Affiliations

  1. Images, Signals and Intelligence Systems Laboratory, University PARIS-EST Creteil (UPEC), LISSI EA 3956, Paris 12, France

    Kurosh Madani

  2. Departamento de Engenharia Informatica Polo II - Pinhal de Marrocos, University of Coimbra, 3030, Coimbra, Portugal

    António Dourado Correia

  3. Evolutionary Systems and Biomedical Engineering Lab, Instituto Superior Tecnico IST Systems and Robotics Institute, Av. Rovisco Pais, 1049-001, Lisboa, Portugal

    Agostinho Rosa

  4. Polytechnic Institute of Setúbal / INSTICC, 2910-595, Setubal, Portugal

    Joaquim Filipe

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Paperin, G., Sadedin, S. (2011). Dual Phase Evolution as a Framework for Understanding Complex Adaptive Systems. In: Madani, K., Correia, A.D., Rosa, A., Filipe, J. (eds) Computational Intelligence. IJCCI 2009. Studies in Computational Intelligence, vol 343. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20206-3_10

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  • DOI: https://doi.org/10.1007/978-3-642-20206-3_10

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-20205-6

  • Online ISBN: 978-3-642-20206-3

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