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We study the problem of finding the Nash equilibrium in a two-player zero-sum Markov game. Due to its formulation as a minimax optimization program, a natural approach to solve the problem is to perform gradient descent/ascent with respect…

Optimization and Control · Mathematics 2022-10-13 Sihan Zeng , Thinh T. Doan , Justin Romberg

This paper studies the approximation of optimal control policies by quantized (discretized) policies for a very general class of Markov decision processes (MDPs). The problem is motivated by applications in networked control systems,…

Optimization and Control · Mathematics 2015-05-14 Naci Saldi , Serdar Yüksel , Tamás Linder

First order kinetic mean field games formally describe the Nash equilibria of deterministic differential games where agents control their acceleration, asymptotically in the limit as the number of agents tends to infinity. The known results…

Analysis of PDEs · Mathematics 2022-07-12 Megan Griffin-Pickering , Alpár R. Mészáros

Recent extensions to dynamic games of the well-known fictitious play learning procedure in static games were proved to globally converge to stationary Nash equilibria in two important classes of dynamic games (zero-sum and…

Computer Science and Game Theory · Computer Science 2022-07-08 Lucas Baudin , Rida Laraki

Policy gradient methods enjoy strong practical performance in numerous tasks in reinforcement learning. Their theoretical understanding in multiagent settings, however, remains limited, especially beyond two-player competitive and potential…

Computer Science and Game Theory · Computer Science 2023-12-22 Ioannis Anagnostides , Ioannis Panageas , Gabriele Farina , Tuomas Sandholm

This paper proposes a distributed algorithm to find the Nash equilibrium in a class of non-cooperative convex games with partial-decision information. Our method employs a distributed projected gradient play approach alongside consensus…

Computer Science and Game Theory · Computer Science 2024-12-13 Duong Thuy Anh Nguyen , Duong Tung Nguyen , Angelia Nedić

Semi-Markov model is one of the most general models for stochastic dynamic systems. This paper deals with a two-person zero-sum game for semi-Markov processes. We focus on the expected discounted payoff criterion with state-action-dependent…

Computer Science and Game Theory · Computer Science 2021-03-09 Zhihui Yu , Xianping Guo , Li Xia

This paper investigates design of noncooperative games from an optimization and control theoretic perspective. Pricing mechanisms are used as a design tool to ensure that the Nash equilibrium of a fairly general class of noncooperative…

Computer Science and Game Theory · Computer Science 2010-07-02 Tansu Alpcan , Lacra Pavel , Nem Stefanovic

This paper aims to design a distributed coordination algorithm for solving a multi-agent decision problem with a hierarchical structure. The primary goal is to search the Nash equilibrium of a noncooperative game such that each player has…

Optimization and Control · Mathematics 2022-05-17 Xiaoyu Ma , Jinlong Lei , Peng Yi , Jie Chen

We consider coalition formation among players in an n-player finite strategic game over infinite horizon. At each time a randomly formed coalition makes a joint deviation from a current action profile such that at new action profile all…

Computer Science and Game Theory · Computer Science 2015-06-11 Konstantin Avrachenkov , Vikas Vikram Singh

The theory of mean field games is a tool to understand noncooperative dynamic stochastic games with a large number of players. Much of the theory has evolved under conditions ensuring uniqueness of the mean field game Nash equilibrium.…

Optimization and Control · Mathematics 2019-03-19 Bruce Hajek , Michael Livesay

While multi-agent reinforcement learning (MARL) has produced numerous algorithms that converge to Nash or related equilibria, such equilibria are often non-unique and can exhibit widely varying efficiency. This raises a fundamental…

Computer Science and Game Theory · Computer Science 2026-01-29 Runyu Zhang , Gioele Zardini , Asuman Ozdaglar , Jeff Shamma , Na Li

This paper considers a time-varying game with $N$ players. Every time slot, players observe their own random events and then take a control action. The events and control actions affect the individual utilities earned by each player. The…

Computer Science and Game Theory · Computer Science 2014-02-04 Michael J. Neely

Stochastic games with discounted payoff, introduced by Shapley, model adversarial interactions in stochastic environments where two players try to optimize a discounted sum of rewards. In this model, long-term weights are geometrically…

Computer Science and Game Theory · Computer Science 2021-10-22 Taylor Dohmen , Ashutosh Trivedi

This paper addresses a class of network games played by dynamic agents using their outputs. Unlike most existing related works, the Nash equilibrium in this work is defined by functions of agent outputs instead of full agent states, which…

Optimization and Control · Mathematics 2023-04-27 Meichen Guo , Claudio De Persis

We address payoff-based decentralized learning in infinite-horizon zero-sum Markov games. In this setting, each player makes decisions based solely on received rewards, without observing the opponent's strategy or actions nor sharing…

Computer Science and Game Theory · Computer Science 2025-02-11 Reda Ouhamma , Maryam Kamgarpour

We consider a class of nonsmooth aggregative games over networks in stochastic regimes, where each player is characterized by a composite cost function $f_i+r_i$, $f_i$ is a smooth expectation-valued function dependent on its own strategy…

Optimization and Control · Mathematics 2024-06-28 Jinlong Lei , Uday V. Shanbhag , Jie Chen

In this paper, the problem of smart grid energy management under stochastic dynamics is investigated. In the considered model, at the demand side, it is assumed that customers can act as prosumers who own renewable energy sources and can…

Computer Science and Game Theory · Computer Science 2017-08-08 Seyed Rasoul Etesami , Walid Saad , Narayan Mandayam , H. Vincent Poor

We consider a symmetric $n$-player nonzero-sum stochastic differential game with controlled jumps and mean-field type interaction among the players. Each player minimizes some expected cost by affecting the drift as well as the jump part of…

Probability · Mathematics 2018-05-14 Chiara Benazzoli , Luciano Campi , Luca Di Persio

We consider a class of continuous-time dynamic games involving a large number of players. Each player selects actions from a finite set and evolves through a finite set of states. State transitions occur stochastically and depend on the…

Systems and Control · Electrical Eng. & Systems 2025-11-12 Leonardo Pedroso , Andrea Agazzi , W. P. M. H. Heemels , Mauro Salazar
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