English

A tutorial on Zero-sum Stochastic Games

Optimization and Control 2019-05-17 v1 Probability

Abstract

Zero-sum stochastic games generalize the notion of Markov Decision Processes (i.e. controlled Markov chains, or stochastic dynamic programming) to the 2-player competitive case : two players jointly control the evolution of a state variable, and have opposite interests. These notes constitute a short mathematical introduction to the theory of such games. Section 1 presents the basic model with finitely many states and actions. We give proofs of the standard results concerning : the existence and formulas for the values of the n-stage games, of the λ\lambda-discounted games, the convergence of these values when λ\lambda goes to 0 (algebraic approach) and when n goes to +\infty, an important example called 'The Big Match' and the existence of the uniform value. Section 2 presents a short and subjective selection of related and more recent results : 1-player games (MDP) and the compact non expansive case, a simple compact continuous stochastic game with no asymptotic value, and the general equivalence between the uniform convergence of (v n) n and (v λ\lambda) λ\lambda. More references on the topic can be found for instance in the books by Mertens-Sorin

Keywords

Cite

@article{arxiv.1905.06577,
  title  = {A tutorial on Zero-sum Stochastic Games},
  author = {Jérôme Renault},
  journal= {arXiv preprint arXiv:1905.06577},
  year   = {2019}
}