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Foundations of Complex Systems

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  • Nicolis, Gregoire
  • Nicolis, Catherine

Abstract

An approach to Complexity from the perspective of fundamental science is outlined, drawing on the cross-fertilization of concepts and tools from nonlinear dynamics, statistical physics, probability and information theories, data analysis and numerical simulation. Emphasis is placed on the intertwining between different levels of description and on the probabilistic dimension of complex systems, in connection with the issue of prediction.

Suggested Citation

  • Nicolis, Gregoire & Nicolis, Catherine, 2009. "Foundations of Complex Systems," European Review, Cambridge University Press, vol. 17(2), pages 237-248, May.
    • Handle: RePEc:cup:eurrev:v:17:y:2009:i:02:p:237-248_00
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    Cited by:

    1. Rika Preiser & Reinette Biggs & Maike Hamann & Nadia Sitas & Odirilwe Selomane & Joy Waddell & Hayley Clements & Tanja Hichert, 2021. "Co‐exploring relational heuristics for sustainability transitions towards more resilient and just Anthropocene futures," Systems Research and Behavioral Science, Wiley Blackwell, vol. 38(5), pages 625-634, October.
    2. Chansoo Kim & Daniel S Kim & Kwangwon Ahn & M Y Choi, 2017. "Dynamics of analyst forecasts and emergence of complexity: Role of information disparity," PLOS ONE, Public Library of Science, vol. 12(5), pages 1-18, May.

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