Ecodynamics pp 95-100 | Cite as

Collective Intelligence in Evolving Systems

  • H.-P. Schwefel
Part of the Research Reports in Physics book series (RESREPORTS)


Ecosystems, comprising diverse living beings with complex, ever changing, compartments and interrelationships, cannot be handled sufficiently by the same kind of models as mechanical systems. Static or equilibrium models may describe short term adaptation phenomena adequately, but in the long term the openness of ecosystems allows them to reach ever new states and structures. Only evolutionary paradigmata can help in understanding ecodynamics and in developing adequate adaptive management strategies. This has been emphasized by biologists like Dobzhansky C1] as well as social scientists like Boulding [21 Eigen and Winkler-Oswatitsch [3], moreover, have shown how to interprète natural phenomena in the framework of evolutionary chance- and-necessity games. Even if the model, presented here, arose from the inverse goal to use nature’s learning strategy for technical meliorization, it may serve as well to learn about the learning process of ecosystems by comparing the effectiveness of variants of the evolutionary strategies. There have been several attempts to do so [4, 5, 6, 7]


Internal Model Progress Rate Collective Intelligence Optimum Scaling Proper Scaling 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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    Dobzhansky, Th. (1962) Mankind Evolving, Yale University Press, New Haven, ConnecticutGoogle Scholar
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    Schwefel, H.P. (1981) Numerical Optimization of Computer Models, Wiley, ChichesterGoogle Scholar
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    Schwefel, H.P. (1987) Collective Phenomena in Evolutionary Systems, paper presented at the 31st Annual Meeting Problems of Constancy and Change of the Int’l. Society for General Systems Research, Budapest, June 1-5, 1987Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1988

Authors and Affiliations

  • H.-P. Schwefel
    • 1
  1. 1.Fachbereich InformatikUniversität DortmundDortmund 50Fed.Rep.of Germany

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