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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Vydáno v:Operations research letters Ročník 41; číslo 4; s. 357 - 362
Hlavní autoři: Boros, Endre, Elbassioni, Khaled, Gurvich, Vladimir, Makino, Kazuhisa
Médium: Journal Article
Jazyk:angličtina
Vydáno: Elsevier B.V 01.07.2013
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ISSN:0167-6377, 1872-7468
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Abstract 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 games with perfect information and a constant number of random nodes, we obtain a pseudo-polynomial algorithm using discounts.
AbstractList 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 games with perfect information and a constant number of random nodes, we obtain a pseudo-polynomial algorithm using discounts.
Author Makino, Kazuhisa
Gurvich, Vladimir
Boros, Endre
Elbassioni, Khaled
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  givenname: Kazuhisa
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  email: makino@kurims.kyoto-u.ac.jp
  organization: Research Institute for Mathematical Sciences (RIMS), Kyoto University, Kyoto 606-8502, Japan
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Issue 4
Keywords Discounted stochastic games
Zero-sum stochastic games
Markov decision processes
Pseudo-polynomial algorithms
Saddle point
Language English
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SubjectTerms Discounted stochastic games
Markov decision processes
Pseudo-polynomial algorithms
Saddle point
Zero-sum stochastic games
Title On discounted approximations of undiscounted stochastic games and Markov decision processes with limited randomness
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