On discounted approximations of undiscounted stochastic games and Markov decision processes with limited randomness

It is shown that the discount factor needed to solve an undiscounted mean payoff stochastic game to optimality is exponentially close to 1, even in one-player games with a single random node and polynomially bounded rewards and transition probabilities. For the class of the so-called irreducible gam...

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Bibliographic Details

Published in:	Operations research letters Vol. 41; no. 4; pp. 357 - 362
Main Authors:	Boros, Endre, Elbassioni, Khaled, Gurvich, Vladimir, Makino, Kazuhisa
Format:	Journal Article
Language:	English
Published:	Elsevier B.V 01.07.2013
Subjects:	Discounted stochastic games Markov decision processes Pseudo-polynomial algorithms Saddle point Zero-sum stochastic games Discounted stochastic games Zero-sum stochastic games Markov decision processes Pseudo-polynomial algorithms Saddle point
ISSN:	0167-6377, 1872-7468
Online Access:	Get full text
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