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We examine the problem of the existence of optimal deterministic stationary strategiesintwo-players antagonistic (zero-sum) perfect information stochastic games with finitely many states and actions.We show that the existenceof such…

Computer Science and Game Theory · Computer Science 2016-11-28 Hugo Gimbert , Wieslaw Zielonka

It was shown in Flesch and Solan (2022) with a rather involved proof that all two-player stochastic games with finite state and action spaces and shift-invariant payoffs admit an $\epsilon$-equilibrium, for every $\epsilon>0$. Their proof…

Optimization and Control · Mathematics 2022-08-25 Galit Ashkenazi-Golan , János Flesch , Eilon Solan

In this paper we study how to play (stochastic) games optimally using little space. We focus on repeated games with absorbing states, a type of two-player, zero-sum concurrent mean-payoff games. The prototypical example of these games is…

Computer Science and Game Theory · Computer Science 2016-04-27 Kristoffer Arnsfelt Hansen , Rasmus Ibsen-Jensen , Michal Koucký

We study stochastic zero-sum games on graphs, which are prevalent tools to model decision-making in presence of an antagonistic opponent in a random environment. In this setting, an important question is the one of strategy complexity: what…

Computer Science and Game Theory · Computer Science 2024-02-14 Patricia Bouyer , Youssouf Oualhadj , Mickael Randour , Pierre Vandenhove

An ideal strategy in zero-sum games should not only grant the player an average reward no less than the value of Nash equilibrium, but also exploit the (adaptive) opponents when they are suboptimal. While most existing works in Markov games…

Machine Learning · Computer Science 2022-06-15 Qinghua Liu , Yuanhao Wang , Chi Jin

Blackwell's approachability (Blackwell, 1954, 1956) is a very general online learning framework where a Decision Maker obtains vector-valued outcomes, and aims at the convergence of the average outcome to a given ``target'' set. Blackwell…

Optimization and Control · Mathematics 2024-08-26 Joon Kwon , Yijun Wan , Bruno Ziliotto

In optimal stopping problems, a Markov structure guarantees Markovian optimal stopping times (first exit times). Surprisingly, there is no analogous result for Markovian stopping games once randomization is required. This paper addresses…

Probability · Mathematics 2024-08-02 Sören Christensen , Boy Schultz

We study nonzero-sum stochastic games for continuous time Markov decision processes on a denumerable state space with risk-sensitive ergodic cost criterion. Transition rates and cost rates are allowed to be unbounded. Under a Lyapunov type…

Optimization and Control · Mathematics 2022-07-18 Mrinal K Ghosh , Subrata Golui , Chandan Pal , Somnath Pradhan

We prove that zero-sum Dynkin games in continuous time with partial and asymmetric information admit a value in randomised stopping times when the stopping payoffs of the players are general \cadlag measurable processes. As a by-product of…

Probability · Mathematics 2022-06-08 Tiziano De Angelis , Nikita Merkulov , Jan Palczewski

We consider a nonzero-sum Markov game on an abstract measurable state space with compact metric action spaces. The goal of each player is to maximize his respective discounted payoff function under the condition that some constraints on a…

Optimization and Control · Mathematics 2021-09-28 François Dufour , Tomás Prieto-Rumeau

We consider a nonzero-sum N-player Markov game on an abstract measurable state space with compact metric action spaces. The payoff functions are bounded Carath\'eodory functions and the transitions of the system are assumed to have a…

Optimization and Control · Mathematics 2023-05-09 François Dufour , Tomás Prieto-Rumeau

We consider time-homogeneous uniformly nondegenerate stochastic differential games in domains and propose constructing $\varepsilon$-optimal strategies and policies by using adjoint Markov strategies and adjoint Markov policies which are…

Optimization and Control · Mathematics 2019-03-26 N. V. Krylov

We prove that every two-player nonzero-sum stopping game in discrete time admits an \epsilon-equilibrium in randomized strategies for every \epsilon >0. We use a stochastic variation of Ramsey's theorem, which enables us to reduce the…

Probability · Mathematics 2007-05-23 Eran Shmaya , Eilon Solan

We study online reinforcement learning in average-reward stochastic games (SGs). An SG models a two-player zero-sum game in a Markov environment, where state transitions and one-step payoffs are determined simultaneously by a learner and an…

Machine Learning · Computer Science 2017-12-05 Chen-Yu Wei , Yi-Te Hong , Chi-Jen Lu

Stochastic games are an important class of problems that generalize Markov decision processes to game theoretic scenarios. We consider finite state two-player zero-sum stochastic games over an infinite time horizon with discounted rewards.…

Optimization and Control · Mathematics 2008-06-17 Parikshit Shah , Pablo A. Parrilo

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…

Optimization and Control · Mathematics 2019-05-17 Jérôme Renault

The existence of stationary Markov perfect equilibria in stochastic games is shown under a general condition called "(decomposable) coarser transition kernels". This result covers various earlier existence results on correlated equilibria,…

Optimization and Control · Mathematics 2017-01-24 Wei He , Yeneng Sun

Establishing the existence of exact or near Markov or stationary perfect Nash equilibria in nonzero-sum Markov games over Borel spaces is a challenging problem with limited positive results. Motivated by problems in multi-agent and Bayesian…

Systems and Control · Electrical Eng. & Systems 2025-07-22 Naci Saldi , Gurdal Arslan , Serdar Yuksel

In this paper, we consider a large class of constrained non-cooperative stochastic Markov games with countable state spaces and discounted cost criteria. In one-player case, i.e., constrained discounted Markov decision models, it is…

Optimization and Control · Mathematics 2021-12-16 Anna Jaśkiewicz , Andrzej S. Nowak

In this paper we consider two-person zero-sum risk-sensitive stochastic dynamic games with Borel state and action spaces and bounded reward. The term risk-sensitive refers to the fact that instead of the usual risk neutral optimization…

Optimization and Control · Mathematics 2021-07-21 Nicole Bäuerle , Ulrich Rieder
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