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Complex landscapes of spatial interaction

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  • David F. Batten

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    (The Temaplan Group P.O. Box 3026, Dendy Brighton 3186, Australia)

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    Abstract

    How complex is the spatial economy? Some apostles of complexity argue that complex behaviour can arise in any system consisting of a largish number of intelligent, adaptive agents interacting on the basis of local information only. This paper examines several features of such dynamic systems, including path-dependence, emergence and self-organization. It goes on to explore their importance for the spatial sciences. Because space scales can change abruptly from local to global, strongly-interactive spatial economies sometimes exhibit astonishing collective properties, emergent features which are lawful in their own right. Segregation, self-similarity and the rank-size rule are familiar examples. To understand how collective order arises from seemingly random fluctuations, we must note how agents choose to interact with other agents and with their environment. We must synthesize rather than analyse. In the paper, self-organization is explored in a variety of contexts, including Schelling's model of neighborhood segregation and some work with cellular automata that has sharpened our insights into the collective synthesis of agents' interactions. Power laws are widely observed. A new way of doing social science - agent-based simulation - offers powerful new insights. It seems likely to revolutionize our field, along with the whole of the social sciences. Some of the current research underway in this area is discussed. "Truth is much too complicated to allow anything but approximations." John von Neumann

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    Bibliographic Info

    Article provided by Springer in its journal The Annals of Regional Science.

    Volume (Year): 35 (2001)
    Issue (Month): 1 ()
    Pages: 81-111

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    Handle: RePEc:spr:anresc:v:35:y:2001:i:1:p:81-111

    Note: Received: February 1999/Accepted: January 2000
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    Cited by:
    1. Juan Miguel Benito & Penélope Hernández, 2007. "Modelling Segregation Through Cellular Automata: A Theoretical Answer," Working Papers. Serie AD 2007-16, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    2. Elsner, Wolfram & Heinrich, Torsten, 2009. "A simple theory of 'meso'. On the co-evolution of institutions and platform size--With an application to varieties of capitalism and 'medium-sized' countries," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 38(5), pages 843-858, October.
    3. Wolfram Elsner, 2010. "The process and a simple logic of ‘meso’. Emergence and the co-evolution of institutions and group size," Journal of Evolutionary Economics, Springer, vol. 20(3), pages 445-477, June.
    4. Ron Martin & Peter Sunley, 2007. "Complexity thinking and evolutionary economic geography," Journal of Economic Geography, Oxford University Press, vol. 7(5), pages 573-601, September.
    5. He, Zheng & Rayman-Bacchus, Lez & Wu, Yiming, 2011. "Self-organization of industrial clustering in a transition economy: A proposed framework and case study evidence from China," Research Policy, Elsevier, vol. 40(9), pages 1280-1294.
    6. Boschma, Ron & Frenken, Koen, 2002. "Why is economic geography an evolutionary science?," ERSA conference papers ersa02p320, European Regional Science Association.

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