LEARNING IN BAYESIAN GAMES BY BOUNDED RATIONAL PLAYERS I

Taesung Kim and Nicholas C. Yannelis

Macroeconomic Dynamics, 1997, vol. 1, issue 3, 568-587

Abstract: We study learning in Bayesian games (or games with differential information) with an arbitrary number of bounded rational players, i.e., players who choose approximate best response strategies [approximate Bayesian Nash Equilibrium (BNE) strategies] and who also are allowed to be completely irrational in some states of the world. We show that bounded rational players by repetition can reach a limit full information BNE outcome. We also prove the converse, i.e., given a limit full information BNE outcome, we can construct a sequence of bounded rational plays that converges to the limit full information BNE outcome.

Date: 1997
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