Premium
Bayesian Learning, Smooth Approximate Optimal Behavior, and Convergence to ε ‐Nash Equilibrium
Author(s) -
Noguchi Yuichi
Publication year - 2015
Publication title -
econometrica
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 16.7
H-Index - 199
eISSN - 1468-0262
pISSN - 0012-9682
DOI - 10.3982/ecta9332
Subject(s) - nash equilibrium , convergence (economics) , mathematical economics , economics , best response , epsilon equilibrium , mathematics , mathematical optimization , macroeconomics
In this paper, I construct players' prior beliefs and show that these prior beliefs lead the players to learn to play an approximate Nash equilibrium uniformly in any infinitely repeated slightly perturbed game with discounting and perfect monitoring. That is, given any ε > 0, there exists a (single) profile of players' prior beliefs that leads play to almost surely converge to an ε ‐Nash equilibrium uniformly for any (finite normal form) stage game with slight payoff perturbation and any discount factor less than 1.