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We study two-player zero-sum concurrent stochastic games with finite state and action space played for an infinite number of steps. In every step, the two players simultaneously and independently choose an action. Given the current state…

Computer Science and Game Theory · Computer Science 2024-10-10 Ali Asadi , Krishnendu Chatterjee , Raimundo Saona , Jakub Svoboda

We consider concurrent games played on graphs. At every round of a game, each player simultaneously and independently selects a move; the moves jointly determine the transition to a successor state. Two basic objectives are the safety…

Computer Science and Game Theory · Computer Science 2008-09-25 Krishnendu Chatterjee , Luca de Alfaro , Thomas A. Henzinger

Two-player zero-sum repeated games are well understood. Computing the value of such a game is straightforward. Additionally, if the payoffs are dependent on a random state of the game known to one, both, or neither of the players, the…

Information Theory · Computer Science 2009-11-05 Paul Cuff

We present an approach for systematically anticipating the actions and policies employed by \emph{oblivious} environments in concurrent stochastic games, while maximizing a reward function. Our main contribution lies in the synthesis of a…

Artificial Intelligence · Computer Science 2024-09-19 Shadi Tasdighi Kalat , Sriram Sankaranarayanan , Ashutosh Trivedi

We consider two-player stochastic games played on a finite graph for infinitely many rounds. Stochastic games generalize both Markov decision processes (MDP) by adding an adversary player, and two-player deterministic games by adding…

Computer Science and Game Theory · Computer Science 2022-02-28 Laurent Doyen

A model of stochastic games where multiple controllers jointly control the evolution of the state of a dynamic system but have access to different information about the state and action processes is considered. The asymmetry of information…

Computer Science and Game Theory · Computer Science 2012-09-18 Ashutosh Nayyar , Abhishek Gupta , Cédric Langbort , Tamer Başar

We study the value and the optimal strategies for a two-player zero-sum optimal stopping game with incomplete and asymmetric information. In our Bayesian set-up, the drift of the underlying diffusion process is unknown to one player…

Probability · Mathematics 2020-07-15 Tiziano De Angelis , Erik Ekström , Kristoffer Glover

In this paper, we extend the Descent framework, which enables learning and planning in the context of two-player games with perfect information, to the framework of stochastic games. We propose two ways of doing this, the first way…

Artificial Intelligence · Computer Science 2023-02-10 Quentin Cohen-Solal , Tristan Cazenave

We provide a self-contained introduction to finite extensive games with perfect information. In these games players proceed in turns having, at each stage, finitely many moves to their disposal, each play always ends, and in each play the…

Computer Science and Game Theory · Computer Science 2022-04-20 Krzysztof R. Apt , Sunil Simon

We study a class of two-player competitive concurrent stochastic games on graphs with reachability objectives. Specifically, player 1 aims to reach a subset $F_1$ of game states, and player 2 aims to reach a subset $F_2$ of game states…

Systems and Control · Electrical Eng. & Systems 2023-03-24 Chongyang Shi , Shuo Han , Jie Fu

Many important real-world settings contain multiple players interacting over an unknown duration with probabilistic state transitions, and are naturally modeled as stochastic games. Prior research on algorithms for stochastic games has…

Computer Science and Game Theory · Computer Science 2021-02-19 Sam Ganzfried

Two-player stochastic games are games with two 2 players and a randomised entity called "nature". A natural question to ask in this framework is the existence of strategies that ensure that an event happens with probability 1 (almost-sure…

Computer Science and Game Theory · Computer Science 2018-06-27 Youssouf Oualhadj , Léo Tible , Daniele Varacca

In imperfect-information games, agents must make decisions based on partial knowledge of the game state. The Belief Stochastic Game model addresses this challenge by delegating state estimation to the game model itself. This allows agents…

Artificial Intelligence · Computer Science 2025-08-20 Achille Morenville , Éric Piette

We study zero-sum differential games with state constraints and one-sided information, where the informed player (Player 1) has a categorical payoff type unknown to the uninformed player (Player 2). The goal of Player 1 is to minimize his…

Computer Science and Game Theory · Computer Science 2024-06-05 Mukesh Ghimire , Lei Zhang , Zhe Xu , Yi Ren

We study two-player games on finite graphs. Turn-based games have many nice properties, but concurrent games are harder to tame: e.g. turn-based stochastic parity games have positional optimal strategies, whereas even basic concurrent…

Computer Science and Game Theory · Computer Science 2023-11-27 Benjamin Bordais , Patricia Bouyer , Stéphane Le Roux

We compare two approaches for modelling imperfect information in infinite games by using finite-state automata. The first, more standard approach views information as the result of an observation process driven by a sequential Mealy…

Computer Science and Game Theory · Computer Science 2020-01-31 Dietmar Berwanger , Laurent Doyen

The overall aim of our research is to develop techniques to reason about the equilibrium properties of multi-agent systems. We model multi-agent systems as concurrent games, in which each player is a process that is assumed to act…

Logic in Computer Science · Computer Science 2020-08-14 Julian Gutierrez , Aniello Murano , Giuseppe Perelli , Sasha Rubin , Thomas Steeples , Michael Wooldridge

We consider extensive games with perfect information with well-founded game trees and study the problems of existence and of characterization of the sets of subgame perfect equilibria in these games. We also provide such characterizations…

Computer Science and Game Theory · Computer Science 2021-06-23 Krzysztof R. Apt , Sunil Simon

We give an algorithm for solving stochastic parity games with almost-sure winning conditions on lossy channel systems, for the case where the players are restricted to finite-memory strategies. First, we describe a general framework, where…

Computer Science and Game Theory · Computer Science 2013-06-14 Parosh Aziz Abdulla , Lorenzo Clemente , Richard Mayr , Sven Sandberg

We study Markov decision processes and turn-based stochastic games with parity conditions. There are three qualitative winning criteria, namely, sure winning, which requires all paths must satisfy the condition, almost-sure winning, which…

Logic in Computer Science · Computer Science 2018-04-11 Krishnendu Chatterjee , Nir Piterman