Title
A Potential Reduction Algorithm for Two-person Zero-sum Mean Payoff Stochastic Games
Abstract
We suggest a new algorithm for two-person zero-sum undiscounted stochastic games focusing on stationary strategies. Given a positive real \(\varepsilon \), let us call a stochastic game \(\varepsilon \)-ergodic, if its values from any two initial positions differ by at most \(\varepsilon \). The proposed new algorithm outputs for every \(\varepsilon >0\) in finite time either a pair of stationary strategies for the two players guaranteeing that the values from any initial positions are within an \(\varepsilon \)-range, or identifies two initial positions u and v and corresponding stationary strategies for the players proving that the game values starting from u and v are at least \(\varepsilon /24\) apart. In particular, the above result shows that if a stochastic game is \(\varepsilon \)-ergodic, then there are stationary strategies for the players proving \(24\varepsilon \)-ergodicity. This result strengthens and provides a constructive version of an existential result by Vrieze (Stochastic games with finite state and action spaces. PhD thesis, Centrum voor Wiskunde en Informatica, Amsterdam, 1980) claiming that if a stochastic game is 0-ergodic, then there are \(\varepsilon \)-optimal stationary strategies for every \(\varepsilon > 0\). The suggested algorithm is based on a potential transformation technique that changes the range of local values at all positions without changing the normal form of the game.
Year
DOI
Venue
2015
10.1007/s13235-016-0199-x
Dynamic Games and Applications
Keywords
Field
DocType
Undiscounted stochastic games, Limiting average payoff, Mean payoff, Local reward, Potential transformation, Computational game theory
Ergodicity,Mathematical economics,Combinatorics,Computational game theory,Constructive,Algorithm,Finite state,Mathematics,Finite time,Stochastic game
Journal
Volume
Issue
ISSN
abs/1508.03455
1
2153-0793
Citations 
PageRank 
References 
0
0.34
14
Authors
4
Name
Order
Citations
PageRank
Endre Boros11779155.63
khaled elbassioni247335.78
Vladimir Gurvich368868.89
Kazuhisa Makino41088102.74