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Learning In Bayesian Games By Bounded Rational Players I

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  • KIM, TAESUNG
  • YANNELIS, NICHOLAS C.

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.

Suggested Citation

  • Kim, Taesung & Yannelis, Nicholas C., 1997. "Learning In Bayesian Games By Bounded Rational Players I," Macroeconomic Dynamics, Cambridge University Press, vol. 1(3), pages 568-587, September.
    • Handle: RePEc:cup:macdyn:v:1:y:1997:i:03:p:568-587_00
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