The Exponential Convergence of Bayesian Learning in Normal Form Games
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Center for Economic Research, Department of Economics, University of Minnesota
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This paper continues the study of Bayesian learning processes for general finite-player,
finite-strategy normal form games. Bayesian learning was introduced in an earlier
paper by the present author as an iterative mechanism by which players can learn Nash
equilibria. The main result of the present paper is that if prior beliefs are sufficiently
uniform and expectations converge to a "regular" Nash equilibrium, then the rate of convergence
is exponential.
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Discussion Paper
259
259
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Jordan, J.S., (1990), "The Exponential Convergence of Bayesian Learning in Normal Form Games", Discussion Paper No. 259, Center for Economic Research, Department of Economics, University of Minnesota.
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Jordan, James S.. (1990). The Exponential Convergence of Bayesian Learning in Normal Form Games. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/55541.
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