Working paper

Learning in Bayesian games with binary actions

Abstract:: This paper considers a simple adaptive learning rule in Bayesian games where players employ threshold strategies. Global convergence results are given for supermodular games and potentital games.

Publication status:: Published

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APA Style

Beggs, A. (2005). Learning in Bayesian games with binary actions. University of Oxford.

MLA Style

Beggs, A. “Learning in Bayesian Games with Binary Actions.” University of Oxford, 2005. Department of Economics Discussion Paper Series.

Chicago Style

Beggs, A. 2005. “Learning in Bayesian Games with Binary Actions.” Department of Economics Discussion Paper Series. University of Oxford.
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Files:: d17f45d4-c59b-4b58-adac-fc77f7ffcf0e

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Authors

+ Beggs, A More by this author

Role:: Author

Publisher:: University of Oxford
Series:: Department of Economics Discussion Paper Series
Publication date:: 2005-04-01
Paper number:: 232

Keywords:: learning

binary actions

Bayesian games

passive stochastic approximation
Pubs id:: 1144198
Local pid:: pubs:1144198
Deposit date:: 2020-12-15
ARK identifier:: ark:/29072/ora_650d8e29668e427c9edb8810b8e362a4

Terms of use

Copyright date:: 2005
Rights statement:: Copyright 2005 The Author(s)

Licence:: Terms and Conditions of Use for Oxford University Research Archive

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