Learning in Bayesian Games with Binary Actions

This paper considers a simple adaptive learning rule in Bayesian games where players employ threshold strategies. Global convergence results are given for supermodular games and potentital games.

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Year of publication:	2005-04-01
Authors:	Beggs, Alan
Institutions:	Department of Economics, Oxford University
Subject:	Bayesian Games \| Learning \| Binary Actions \| Passive Stochastic Approximation

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Extent:	application/pdf
Series:	Economics Series Working Papers.
Type of publication:	Book / Working Paper
Language:	English
Notes:	Number 232
Classification:	C72 - Noncooperative Games ; D83 - Search, Learning, Information and Knowledge
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10005047697