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Stochastic two-player games model systems with an environment that is both adversarial and stochastic. In this paper, we study the expected value of bounded quantitative prefix-independent objectives in the context of stochastic games. We…

Computer Science and Game Theory · Computer Science 2025-08-01 Laurent Doyen , Pranshu Gaba , Shibashis Guha

Two-player (antagonistic) games on (possibly stochastic) graphs are a prevalent model in theoretical computer science, notably as a framework for reactive synthesis. Optimal strategies may require randomisation when dealing with inherently…

Computer Science and Game Theory · Computer Science 2024-11-25 James C. A. Main , Mickael Randour

We show that the problem of deciding whether in a multi-player perfect information recursive game (i.e. a stochastic game with terminal rewards) there exists a stationary Nash equilibrium ensuring each player a certain payoff is Existential…

Computer Science and Game Theory · Computer Science 2020-08-19 Kristoffer Arnsfelt Hansen , Steffan Christ Sølvsten

We show that computing approximate stationary Markov coarse correlated equilibria (CCE) in general-sum stochastic games is computationally intractable, even when there are two players, the game is turn-based, the discount factor is an…

Machine Learning · Computer Science 2022-04-11 Constantinos Daskalakis , Noah Golowich , Kaiqing Zhang

This paper considers information sharing in a multi-player repeated game. Every round, each player observes a subset of components of a random vector and then takes a control action. The utility earned by each player depends on the full…

Optimization and Control · Mathematics 2014-12-31 Michael J. Neely

Stochastic optimal control with unknown randomness distributions has been studied for a long time, encompassing robust control, distributionally robust control, and adaptive control. We propose a new episodic Bayesian approach that…

Optimization and Control · Mathematics 2025-06-02 Alexander Shapiro , Enlu Zhou , Yifan Lin , Yuhao Wang

We examine perfect information stochastic mean-payoff games - a class of games containing as special sub-classes the usual mean-payoff games and parity games. We show that deterministic memoryless strategies that are optimal for discounted…

Computer Science and Game Theory · Computer Science 2010-06-09 Hugo Gimbert , Wiesław Zielonka

We consider infinite-state turn-based stochastic games of two players, Box and Diamond, who aim at maximizing and minimizing the expected total reward accumulated along a run, respectively. Since the total accumulated reward is unbounded,…

Computer Science and Game Theory · Computer Science 2012-08-09 Tomáš Brázdil , Antonín Kučera , Petr Novotný

In this paper, Nash equilibrium seeking among a network of players is considered. Different from many existing works on Nash equilibrium seeking in non-cooperative games, the players considered in this paper cannot directly observe the…

Optimization and Control · Mathematics 2017-03-28 Maojiao Ye , Guoqiang Hu

Stochastic games combine controllable and adversarial non-determinism with stochastic behavior and are a common tool in control, verification and synthesis of reactive systems facing uncertainty. Multi-objective stochastic games are natural…

Computer Science and Game Theory · Computer Science 2021-09-20 Tobias Winkler , Maximilian Weininger

We propose a game-theoretic framework that incorporates both incomplete information and general ambiguity attitudes on factors external to all players. Our starting point is players' preferences on payoff-distribution vectors, essentially…

Economics · Quantitative Finance 2017-04-04 Jian Yang

Establishing the existence of Nash equilibria for partially observed stochastic dynamic games is known to be quite challenging, with the difficulties stemming from the noisy nature of the measurements available to individual players…

Systems and Control · Computer Science 2018-06-06 Naci Saldi , Tamer Basar , Maxim Raginsky

We devise a policy-iteration algorithm for deterministic two-player discounted and mean-payoff games, that runs in polynomial time with high probability, on any input where each payoff is chosen independently from a sufficiently random…

Computer Science and Game Theory · Computer Science 2024-02-07 Bruno Loff , Mateusz Skomra

The combination of the Bayesian game and learning has a rich history, with the idea of controlling a single agent in a system composed of multiple agents with unknown behaviors given a set of types, each specifying a possible behavior for…

Machine Learning · Computer Science 2024-11-21 Tongxin Li , Tinashe Handina , Shaolei Ren , Adam Wierman

Optimal behavior in (competitive) situation is traditionally determined with the help of utility functions that measure the payoff of different actions. Given an ordering on the space of revenues (payoffs), the classical axiomatic approach…

General Economics · Economics 2020-04-27 Stefan Rass

An extensive literature in economics and social science addresses contests, in which players compete to outperform each other on some measurable criterion, often referred to as a player's score, or output. Players incur costs that are an…

Computer Science and Game Theory · Computer Science 2013-08-01 Leslie Ann Goldberg , Paul W. Goldberg , Piotr Krysta , Carmine Ventre

We study Bayesian coordination games where agents receive noisy private information over the game's payoffs, and over each others' actions. If private information over actions is of low quality, equilibrium uniqueness obtains in a manner…

General Economics · Economics 2021-11-23 Dominik Grafenhofer , Wolfgang Kuhle

We present a novel variant of fictitious play dynamics combining classical fictitious play with Q-learning for stochastic games and analyze its convergence properties in two-player zero-sum stochastic games. Our dynamics involves players…

Computer Science and Game Theory · Computer Science 2022-06-03 Muhammed O. Sayin , Francesca Parise , Asuman Ozdaglar

Previous research has shown how indirect reciprocity can promote cooperation through evolutionary game theoretic models. Most work in this field assumes a separation of time-scales: individuals' reputations equilibrate at a fast time scale…

Populations and Evolution · Quantitative Biology 2024-12-23 Bryce Morsky , Joshua B. Plotkin , Erol Akçay

Stochastic games combine controllable and adversarial non-determinism with stochastic behavior and are a common tool in control, verification and synthesis of reactive systems facing uncertainty. Multi-objective stochastic games are natural…

Computational Complexity · Computer Science 2022-07-21 Tobias Winkler , Maximilian Weininger
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