# A tutorial on Zero-sum Stochastic Games

arXiv: https://arxiv.org/abs/1905.06577 · HTML: https://mlsanity.com/paper/1905.06577/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 16 May 2019.

## Built on by (most cited first, 1 of 1)

- [Bellman Optimality of Average-Reward Robust Markov Decision Processes with a Constant Gain](https://mlsanity.com/paper/2509.14203/) (2025)

## Abstract (arXiv)

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-discounted games, the convergence of these values when λ goes to 0 (algebraic approach) and when n goes to +∞, 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) λ. More references on the topic can be found for instance in the books by Mertens-Sorin