DSpace - Tor Vergata >
Facoltà di Economia >
CEIS - Centre for International Studies on Economic Growth >
Quaderni >

Please use this identifier to cite or link to this item: http://hdl.handle.net/2108/251

Title: A Learning theory for the concept of Harsanyi-Nash equilibrium in stochastic games with Bayesian players
Authors: Leoni, Patrick
Issue Date: May-2003
Publisher: CEIS
Series/Report no.: Quaderni CEIS; 192
Abstract: This paper investigates simultaneous learning about both nature and others’ actions in stochastic games, and identifies a set of sufficient conditions assuring that equilibrium actions played by Bayesian agents become eventually arbitrarily close to a Harsanyi-Nash equilibrium. We assume that players have prior beliefs about both nature’drawings and other players’ strategies, which are not necessarily exact. Provided that 1) every player maximizes his own expected sum of discounted one-period utility against their own beliefs, 2) every player updates his beliefs in a Bayesian manner, 3) prior beliefs about both nature’ drawings and other players’ strategies have a grain of truth and 4) beliefs about nature’ drawings are independent of actions taken by the players during the game, we show that after some finite time the equilibrium outcome of the above game is arbitrarily close to a Harsanyi-Nash equilibrium, where priors beliefs are assumed to be exact. Therefore, the result strictly...
URI: http://hdl.handle.net/2108/251
Appears in Collections:Quaderni

Files in This Item:

File Description SizeFormat
192.pdf233KbAdobe PDFView/Open

Show full item record

All items in DSpace are protected by copyright, with all rights reserved.