Statistics Papers
Document Type
Journal Article
Date of this Version
2-2008
Publication Source
Journal of Computer and System Sciences
Volume
74
Issue
1
Start Page
115
Last Page
130
DOI
10.1016/j.jcss.2007.04.017
Abstract
We provide a natural learning process in which the joint frequency of empirical play converges into the set of convex combinations of Nash equilibria. In this process, all players rationally choose their actions using a public prediction made by a deterministic, weakly calibrated algorithm. Furthermore, the public predictions used in any given round play are frequently close to some Nash equilibrium of the game.
Copyright/Permission Statement
© 2008. This manuscript version is made available under the CC-BY-NC-ND 4.0 license.
Keywords
Nash equilibria, calibration, correlated equilibria, game theory, learning
Recommended Citation
Kakade, S. M., & Foster, D. P. (2008). Deterministic Calibration and Nash Equilibrium. Journal of Computer and System Sciences, 74 (1), 115-130. http://dx.doi.org/10.1016/j.jcss.2007.04.017
Date Posted: 27 November 2017
This document has been peer reviewed.