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Equilibrium selection in the stag hunt game under generalized reinforcement learning

Listed author(s):
  • Lahkar, Ratul
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    We apply the generalized reinforcement (GR) learning protocol to the stag hunt game. GR learning combines positive and negative reinforcement. The GR learning rule generates the GR dynamic, which governs the evolution of the mixed strategy of agents in the population. We identify conditions under which the GR dynamic converges globally to one of the two pure strategy Nash equilibria of the game.

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    File URL: http://www.sciencedirect.com/science/article/pii/S0167268117301051
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    Article provided by Elsevier in its journal Journal of Economic Behavior & Organization.

    Volume (Year): 138 (2017)
    Issue (Month): C ()
    Pages: 63-68

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    Handle: RePEc:eee:jeborg:v:138:y:2017:i:c:p:63-68
    DOI: 10.1016/j.jebo.2017.04.012
    Contact details of provider: Web page: http://www.elsevier.com/locate/jebo

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