THE EXPONENTIAL CONVERGENCE OF BAYESIAN LEARNING IN NORMAL-FORM GAMES

被引：17

作者：

JORDAN, JS

机构：

[1] Department of Economics, University of Minnesota, Minneapolis, MN 55455, 1035 Management and Economics

来源：

GAMES AND ECONOMIC BEHAVIOR | 1992年 / 4卷 / 02期

基金：

美国国家科学基金会;

关键词：

D O I：

10.1016/0899-8256(92)90015-K

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

This paper continues the study of Bayesian learning processes for general finite-player, finite-strategy normal form games. Bayesian learning was introduced in an earlier paper by the present author as an iterative mechanism by which players can learn Nash equilibria. The main result of the present paper is that if prior beliefs are sufficiently uniform and expectations converge to a "regular" Nash equilibrium, then the rate of convergence is exponential. © 1992.

引用

页码：202 / 217

页数：16