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A spectrum of equilibration processes in game theory

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  • Bernard Walliser

    (CERAS-ENPC and CREA-Ecole Polytechnique, 28 rue des Saints-Peres, F-75007 Paris, France)

Abstract

In game theory, four dynamic processes converging towards an equilibrium are distinguished and ordered by way of agents' decreasing cognitive capacities. In the eductive process, each player has enough information to simulate perfectly the others' behavior and gets immediately to the equilibrium. In epistemic learning, each player updates his beliefs about others' future strategies, with regard to their sequentially observed actions. In behavioral learning, each player modifies his own strategies according to the observed payoffs obtained from his past actions. In the evolutionary process, each agent has a fixed strategy and reproduces in proportion to the utilities obtained through stochastic interactions. All along the spectrum, longer term dynamics makes up for weaker rationality, and physical relations substitute for mental interactions. Convergence, if any, is towards an always stronger equilibrium notion and selection of an equilibrium state becomes more sensitive to context and history. The processes can be mixed if associated to different periods, agents or mechanisms and deepened if obtained by formal reasoning principles.

Suggested Citation

  • Bernard Walliser, 1998. "A spectrum of equilibration processes in game theory," Journal of Evolutionary Economics, Springer, vol. 8(1), pages 67-87.
    • Handle: RePEc:spr:joevec:v:8:y:1998:i:1:p:67-87
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    Citations

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    Cited by:

    1. Christoph March, 2011. "Adaptive social learning," PSE Working Papers halshs-00572528, HAL.
    2. Russell Golman & Scott Page, 2010. "Basins of attraction and equilibrium selection under different learning rules," Journal of Evolutionary Economics, Springer, vol. 20(1), pages 49-72, January.
    3. Pierre Garrouste, 2001. "Learning in economics: the Austrian insights," ICER Working Papers 25-2001, ICER - International Centre for Economic Research.
    4. Pierre Garrouste, 2008. "The Austrian roots of the economics of institutions," The Review of Austrian Economics, Springer;Society for the Development of Austrian Economics, vol. 21(4), pages 251-269, December.
    5. Defalvard, Hervé, 2000. "Croyances individuelles et coordination sociale," L'Actualité Economique, Société Canadienne de Science Economique, vol. 76(3), pages 341-364, septembre.
    6. Laslier, Jean-Francois & Topol, Richard & Walliser, Bernard, 2001. "A Behavioral Learning Process in Games," Games and Economic Behavior, Elsevier, vol. 37(2), pages 340-366, November.
    7. Jacques Durieu & Philippe Solal, 2012. "Models of Adaptive Learning in Game Theory," Chapters, in: Richard Arena & Agnès Festré & Nathalie Lazaric (ed.), Handbook of Knowledge and Economics, chapter 11, Edward Elgar Publishing.
    8. Franke, Reiner, 2003. "Reinforcement learning in the El Farol model," Journal of Economic Behavior & Organization, Elsevier, vol. 51(3), pages 367-388, July.
    9. Neil Martin, 2016. "Strategy as Mutually Contingent Choice," SAGE Open, , vol. 6(2), pages 21582440166, May.

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