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Evolution as computation: integrating self-organization with generalized Darwinism

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  • BEINHOCKER, ERIC D.

Abstract

Generalized Darwinism and self-organization have been positioned as competing frameworks for explaining processes of economic and institutional change. Proponents of each view question the ontological validity and explanatory power of the other. This paper argues that information theory, rooted in modern thermodynamics, offers the potential to integrate these two perspectives in a common and rigorous framework. Both evolution and self-organization can be generalized as computational processes that can be applied to human social phenomena. Under this view, evolution is a process of algorithmic search through a combinatorial design space, while self-organization is the result of non-zero sum gains from information aggregation. Evolution depends on the existence of self-organizing forces, and evolution acts on designs for self-organizing structures. The framework yields insights on the role of agency and the emergence of novelty. The paper concludes that information theory may provide a fundamental ontological basis for economic and institutional evolution.

Suggested Citation

  • Beinhocker, Eric D., 2011. "Evolution as computation: integrating self-organization with generalized Darwinism," Journal of Institutional Economics, Cambridge University Press, vol. 7(03), pages 393-423, September.
  • Handle: RePEc:cup:jinsec:v:7:y:2011:i:03:p:393-423_00
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    Cited by:

    1. Rodrick Wallace, 2013. "A new formal approach to evolutionary processes in socioeconomic systems," Journal of Evolutionary Economics, Springer, vol. 23(1), pages 1-15, January.
    2. Timothy J. Foxon & Jonathan Köhler & Jonathan Michie & Christine Oughton, 2013. "Towards a new complexity economics for sustainability," Cambridge Journal of Economics, Oxford University Press, vol. 37(1), pages 187-208.
    3. Wäckerle, Manuel, 2013. "On the bottom-up foundations of the banking-macro nexus," Economics Discussion Papers 2013-5, Kiel Institute for the World Economy (IfW).
    4. Kurt Dopfer, 2013. "Evolutionary Economics," Papers on Economics and Evolution 2013-08, Philipps University Marburg, Department of Geography.
    5. repec:eee:ijrema:v:34:y:2017:i:1:p:46-67 is not listed on IDEAS
    6. Robert, Verónica & Yoguel, Gabriel, 2016. "Complexity paths in neo-Schumpeterian evolutionary economics, structural change and development policies," Structural Change and Economic Dynamics, Elsevier, vol. 38(C), pages 3-14.
    7. Kurt Dopfer & Jason Potts & Andreas Pyka, 2016. "Upward and downward complementarity: the meso core of evolutionary growth theory," Journal of Evolutionary Economics, Springer, vol. 26(4), pages 753-763, October.
    8. G. Blind & A. Pyka, 2014. "The rule approach in evolutionary economics: A methodological template for empirical research," Journal of Evolutionary Economics, Springer, vol. 24(5), pages 1085-1105, November.
    9. Blind, Georg, 2011. "Investigating entrepreneurial spirit with the rule approach: why self-employment is on the decline in Japan," MPRA Paper 66749, University Library of Munich, Germany.
    10. Miguel Vazquez, 2018. "Institutional dynamics in an economy seen as a complex adaptive system," IEFE Working Papers 104, IEFE, Center for Research on Energy and Environmental Economics and Policy, Universita' Bocconi, Milano, Italy.

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