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.
