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相关论文: Hilbert Space-Valued LQ Mean Field Games: An Infin…

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We propose a single-level numerical approach to solve Stackelberg mean field game (MFG) problems. In Stackelberg MFG, an infinite population of agents play a non-cooperative game and choose their controls to optimize their individual…

最优化与控制 · 数学 2024-04-24 Gokce Dayanikli , Mathieu Lauriere

We consider stationary viscous Mean-Field Games systems in the case of local, decreasing and unbounded coupling. These systems arise in ergodic mean-field game theory, and describe Nash equilibria of games with a large number of agents…

偏微分方程分析 · 数学 2016-02-16 Marco Cirant

Finite-state mean-field games (MFGs) arise as limits of large interacting particle systems and are governed by an MFG system, a coupled forward-backward differential equation consisting of a forward Kolmogorov-Fokker-Planck (KFP) equation…

最优化与控制 · 数学 2026-02-16 William Hofgard , Asaf Cohen , Mathieu Laurière

In this paper, we propose an initial value fomulation of the discrete mean field games on finite graphs (Graph MFG), and design a neural network based approach to solve it. Graph MFG describes infinite, non-cooperative and interactive…

数值分析 · 数学 2026-04-08 Yaxin Feng , Yang Xiang , Haomin Zhou

In this paper, we study a class of discrete-time mean-field games under the infinite-horizon risk-sensitive discounted-cost optimality criterion. Risk-sensitivity is introduced for each agent (player) via an exponential utility function. In…

最优化与控制 · 数学 2018-10-08 Naci Saldi , Tamer Basar , Maxim Raginsky

Learning by experience in Multi-Agent Systems (MAS) is a difficult and exciting task, due to the lack of stationarity of the environment, whose dynamics evolves as the population learns. In order to design scalable algorithms for systems…

最优化与控制 · 数学 2020-02-24 Romuald Elie , Julien Pérolat , Mathieu Laurière , Matthieu Geist , Olivier Pietquin

We consider a controlled linear-quadratic (LQ) large-population system with mixture of three types agents: major leader, minor leaders and minor followers. The Stackelberg-Nash-Cournot (SNC) approximate equilibrium is studied by a…

最优化与控制 · 数学 2019-05-28 Kehan Si , James Huang , Zhen Wu

In this paper, we study finite-agent linear-quadratic games on graphs. Specifically, we propose a comprehensive framework that extends the existing literature by incorporating heterogeneous and interpretable player interactions. Compared to…

最优化与控制 · 数学 2025-11-19 Ruimeng Hu , Jihao Long , Haosheng Zhou

Mean-field games with absorption is a class of games, that have been introduced in Campi and Fischer (2018) and that can be viewed as natural limits of symmetric stochastic differential games with a large number of players who, interacting…

概率论 · 数学 2021-11-05 Luciano Campi , Maddalena Ghio , Giulia Livieri

We study mean field games and corresponding $N$-player games in continuous time over a finite time horizon where the position of each agent belongs to a finite state space. As opposed to previous works on finite state mean field games, we…

概率论 · 数学 2018-02-01 Alekos Cecchin , Markus Fischer

Mean field games (MFGs) describe the limit, as $n$ tends to infinity, of stochastic differential games with $n$ players interacting with one another through their common empirical distribution. Under suitable smoothness assumptions that…

概率论 · 数学 2018-04-24 Francois Delarue , Daniel Lacker , Kavita Ramanan

We consider a general class of finite-player stochastic games with mean-field interaction, in which the linear-quadratic cost functional includes linear operators acting on controls in $L^2$. We propose a novel approach for deriving the…

最优化与控制 · 数学 2024-02-16 Eduardo Abi Jaber , Eyal Neuman , Moritz Voß

Mean Field Game (MFG) models implicitly assume "rational expectations", meaning that the heterogeneous agents being modeled correctly know all relevant transition probabilities for the complex system they inhabit. When there is common…

偏微分方程分析 · 数学 2026-02-26 Benjamin Moll , Lenya Ryzhik

This paper studies a new class of dynamic optimization problems of large-population (LP) system which consists of a large number of negligible and coupled agents. The most significant feature in our setup is the dynamics of individual…

最优化与控制 · 数学 2014-03-18 Jianhui Huang , Shujun Wang , Hua Xiao

We study Nash equilibria for a sequence of symmetric $N$-player stochastic games of finite-fuel capacity expansion with singular controls and their mean-field game (MFG) counterpart. We construct a solution of the MFG via a simple iterative…

概率论 · 数学 2022-01-19 Luciano Campi , Tiziano De Angelis , Maddalena Ghio , Giulia Livieri

Recent techniques based on Mean Field Games (MFGs) allow the scalable analysis of multi-player games with many similar, rational agents. However, standard MFGs remain limited to homogeneous players that weakly influence each other, and…

计算机科学与博弈论 · 计算机科学 2023-12-19 Kai Cui , Gökçe Dayanıklı , Mathieu Laurière , Matthieu Geist , Olivier Pietquin , Heinz Koeppl

Mean field type games (MFTGs) describe Nash equilibria between large coalitions: each coalition consists of a continuum of cooperative agents who maximize the average reward of their coalition while interacting non-cooperatively with a…

计算机科学与博弈论 · 计算机科学 2025-07-29 Kai Shao , Jiacheng Shen , Mathieu Laurière

This paper investigates the linear-quadratic-Gaussian (LQG) mean-field game (MFG) for a class of stochastic delay systems. We consider a large population system in which the dynamics of each player satisfies some forward stochastic…

最优化与控制 · 数学 2015-10-05 Na Li , Shujun Wang

Mean Field Games (MFG) have been introduced to tackle games with a large number of competing players. Considering the limit when the number of players is infinite, Nash equilibria are studied by considering the interaction of a typical…

最优化与控制 · 数学 2021-06-14 Mathieu Lauriere

This paper studies mean field games for multi-agent systems with control-dependent multiplicative noises. For the general systems with nonuniform agents, we obtain a set of decentralized strategies by solving an auxiliary limiting optimal…

最优化与控制 · 数学 2019-06-10 Bing-Chang Wang , Yuan-Hua Ni , Huanshui Zhang