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Communication and Self-Organisation in Complex Systems: A Basic Approach

In: Knowledge, Complexity and Innovation Systems

Author

Listed:
  • Frank Schweitzer

    (Real World Computing Partnership — Theoretical Foundation GMD Laboratory)

  • Jörg Zimmermann

    (Real World Computing Partnership — Theoretical Foundation GMD Laboratory)

Abstract

The emergence of complex behaviour in systems consisting of interacting elements is among the most fascinating phenomena of our world. Examples can be found in almost every field of today’s scientific interest, ranging from coherent pattern formation in physical and chemical systems (Feistel and Ebeling 1989; Cladis and Palffy-Muhoray 1995), to the motion of swarms of animals in biology (DeAngelis and Gross 1992) and the behaviour of social groups (Weidlich 1991; Vallacher and Nowak 1994). In the social and life sciences, it has generally been held that the evolution of social systems is determined by numerous factors —cultural, sociological, economic, political, and ecological, etc. However, in recent years, the development of the interdisciplinary ‘science of complexity’ has led to the insight that complex dynamic processes may also result from simple interactions. Moreover, at a certain level of abstraction, one can find many common features between complex structures in very different fields (Schweitzer 1997a, b).

Suggested Citation

  • Frank Schweitzer & Jörg Zimmermann, 2001. "Communication and Self-Organisation in Complex Systems: A Basic Approach," Advances in Spatial Science, in: Manfred M. Fischer & Josef Fröhlich (ed.), Knowledge, Complexity and Innovation Systems, chapter 14, pages 275-296, Springer.
    • Handle: RePEc:spr:adspcp:978-3-662-04546-6_14
    DOI: 10.1007/978-3-662-04546-6_14
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    Cited by:

    1. Itzhak Benenson & Erez Hatna & Ehud Or, 2009. "From Schelling to Spatially Explicit Modeling of Urban Ethnic and Economic Residential Dynamics," Sociological Methods & Research, , vol. 37(4), pages 463-497, May.

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