Zero-sum stochastic games with average payoffs: new optimality conditions
type: Item
instance of: scholarly article
title: Zero-sum stochastic games with average payoffs: new optimality conditions
zbMATH Open document ID: 1192.91026
author: Jie Yang
author: Xianping Guo
publication date: 2009-09-03T00:00:00Z
review text: This paper is devoted to the study of zero-sum Markov games on a countable state space. The authors provide conditions that assure the existence of a value of the game and optimal strategies for both players when the average expected payoff criterion is used. This purpose is achieved by establishing the optimality equation via discounted games. The key assumption in the analysis is the following one: the relative difference of the discounted value is bounded from above and below by a function of a finite weighted norm. This requirement is well-known within a dynamic programming framework and has been extensively used in MDP mdels, see, e.g., \textit{L. I. Sennott} [Stochastic dynamic programming and the control of queueing systems, New York, Wiley (1999; Zbl 0997.93503)], Chapter 7.7 or a recent paper of \textit{X. Guo} and \textit{Q Zhu} [J. Appl. Probab. 43, No. 2, 318--334 (2006; Zbl 1121.90122)].
reviewed by: Anna Jaskiewicz
Mathematics Subject Classification ID: 91A15
Mathematics Subject Classification ID: 91A10
Mathematics Subject Classification ID: 91A05
zbMATH DE Number: 5601616
zbMATH Keywords: zero-sum stochastic games
zbMATH Keywords: expected average payoff
zbMATH Keywords: optimal strategies
MaRDI profile type: Publication
full work available at URL: s10114-009-6274-0
OpenAlex ID: W2086129727
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DOI: 10.1007/S10114-009-6274-0
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published in: Acta Mathematica Sinica, English Series
description: scientific article; zbMATH DE number 5601616