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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

We consider two-player zero-sum games on graphs. These games can be classified on the basis of the information of the players and on the mode of interaction between them. On the basis of information the classification is as follows: (a)…

Computer Science and Game Theory · Computer Science 2015-05-19 Krishnendu Chatterjee , Laurent Doyen , Hugo Gimbert , Thomas A. Henzinger

In this paper, we investigate a partially observable zero sum games where the state process is a discrete time Markov chain. We consider a general utility function in the optimization criterion. We show the existence of value for both…

Optimization and Control · Mathematics 2022-11-16 Arnab Bhabak , Subhamay saha

Many non-trivial sequential decision-making problems are efficiently solved by relying on Bellman's optimality principle, i.e., exploiting the fact that sub-problems are nested recursively within the original problem. Here we show how it…

Artificial Intelligence · Computer Science 2022-11-16 Olivier Buffet , Jilles Dibangoye , Aurélien Delage , Abdallah Saffidine , Vincent Thomas

Two-player zero-sum "graph games" are a central model, which proceeds as follows. A token is placed on a vertex of a graph, and the two players move it to produce an infinite "play", which determines the winner or payoff of the game.…

Computer Science and Game Theory · Computer Science 2022-11-28 Guy Avni , Ismael Jecker , Djordje Zikelic

Partially observable stochastic games provide a rich mathematical paradigm for modeling multi-agent dynamic decision making under uncertainty and partial information. However, they generally do not admit closed-form solutions and are…

Optimization and Control · Mathematics 2020-04-15 Yanling Chang , Chelsea C. White

We consider a finite state, finite action, zero-sum stochastic games with data defining the game lying in the ordered field of algebraic numbers. In both the discounted and the limiting average versions of these games we prove that the…

Optimization and Control · Mathematics 2017-12-18 K. Avrachenkov , V. Ejov , J. A. Filar , A. Moghaddam

Incomplete cooperative games generalise the classical model of cooperative games by omitting the values of some of the coalitions. This allows to incorporate uncertainty into the model and study the underlying games as well as possible…

Computer Science and Game Theory · Computer Science 2025-10-07 Martin Černý , Jan Bok , David Hartman , Milan Hladík

The information decomposition problem requires an additive decomposition of the mutual information between the input and target variables into nonnegative terms. The recently introduced solution to this problem, Information Attribution,…

Information Theory · Computer Science 2022-07-13 Tomáš Kroupa , Sara Vannucci , Tomáš Votroubek

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

This paper investigates the two-person zero-sum stochastic games for piece-wise deterministic Markov decision processes with risk-sensitive finite-horizon cost criterion on a general state space. Here, the transition and cost/reward rates…

Optimization and Control · Mathematics 2024-05-15 Subrata Golui

Game logic is a dynamic modal logic which models strategic two person games; it contains propositional dynamic logic (PDL) as a fragment. We propose an interpretation of game logic based on stochastic effectivity functions. A definition of…

Logic in Computer Science · Computer Science 2014-04-01 Ernst-Erich Doberkat

We generalize the results of Fleming and Souganidis (1989) on zero sum stochastic differential games to the case when the controls are unbounded. We do this by proving a dynamic programming principle using a covering argument instead of…

Optimization and Control · Mathematics 2012-01-17 Erhan Bayraktar , Song Yao

A class of nonzero-sum stochastic dynamic games with imperfect information structure is investigated. The game involves an arbitrary number of players, modeled as homogeneous Markov decision processes, aiming to find a sequential Nash…

Optimization and Control · Mathematics 2019-12-17 Jalal Arabneydi , Amir G. Aghdam

Multiagent decision-making in partially observable environments is usually modelled as either an extensive-form game (EFG) in game theory or a partially observable stochastic game (POSG) in multiagent reinforcement learning (MARL). One…

Artificial Intelligence · Computer Science 2021-09-29 Vojtěch Kovařík , Martin Schmid , Neil Burch , Michael Bowling , Viliam Lisý

We consider zero-sum stochastic games with perfect information and finitely many states and actions. The payoff is computed by a function which associates to each infinite sequence of states and actions a real number. We prove that if the…

Computer Science and Game Theory · Computer Science 2022-03-29 Hugo Gimbert , Edon Kelmendi

This paper studies partially observable two-person zero-sum semi-Markov games under a probability criterion, in which the system state may not be completely observed. It focuses on the probability that the accumulated rewards of player 1…

Optimization and Control · Mathematics 2025-08-26 Xin Wen , Li Xia , Zhihui Yu

In this paper we analyse two-player games by their response graphs. The response graph has nodes which are strategy profiles, with an arc between profiles if they differ in the strategy of a single player, with the direction of the arc…

Computer Science and Game Theory · Computer Science 2023-02-15 Oliver Biggar , Iman Shames

Partially observable Markov decision processes (POMDPs) rely on the key assumption that probability distributions are precisely known. Robust POMDPs (RPOMDPs) alleviate this concern by defining imprecise probabilities, referred to as…

Artificial Intelligence · Computer Science 2024-07-30 Eline M. Bovy , Marnix Suilen , Sebastian Junges , Nils Jansen

We introduce a zero-sum game problem of mean-field type as an extension of the classical zero-sum Dynkin game problem to the case where the payoff processes might depend on the value of the game and its probability law. We establish…

Optimization and Control · Mathematics 2022-05-06 Boualem Djehiche , Roxana Dumitrescu