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Learning in Bayesian Games with Binary Actions.

Abstract:

This paper considers a simple adaptive learning rule in Bayesian games with binary actions where players employ threshold strategies. Global convergence results are given for supermodular games and potential games. If there is a unique equilibrium, players’ strategies converge almost surely to it. Even if there is not, in potential games and in the two-player case in supermodular games, any limit point of the learning process must be an equilibrium. In particular, if equilibria are isolated, ...

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Publisher copy:
10.2202/1935-1704.1452

Authors


Alan Beggs More by this author
Journal:
The B.E. Journal of Theoretical Economics
Volume:
9
Issue:
1(Advances)
Publication date:
2009-09-30
DOI:
URN:
uuid:fdc0220c-0357-41a5-a53f-b5342c3c59a0
Local pid:
oai:economics.ouls.ox.ac.uk:14539
Language:
English

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