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Mean field games (MFG) are dynamic games with infinitely many infinitesimal agents. In this context, we study the efficiency of Nash MFG equilibria: Namely, we compare the social cost of a MFG equilibrium with the minimal cost a global…

最优化与控制 · 数学 2018-02-20 Pierre Cardaliaguet , Catherine Rainer

We present a new combined \textit{mean field control game} (MFCG) problem which can be interpreted as a competitive game between collaborating groups and its solution as a Nash equilibrium between groups. Players coordinate their strategies…

最优化与控制 · 数学 2023-02-16 Andrea Angiuli , Nils Detering , Jean-Pierre Fouque , Mathieu Lauriere , Jimin Lin

Mean field games have traditionally been defined~[1,2] as a model of large scale interaction of players where each player has a private type that is independent across the players. In this paper, we introduce a new model of mean field teams…

系统与控制 · 电气工程与系统科学 2022-10-21 Deepanshu Vasal

The sustainable use of common-pool resources (CPRs) is a major environmental governance challenge because of their possible over-exploitation. Research in this field has overlooked the feedback between user decisions and resource dynamics.…

理论经济学 · 经济学 2021-10-04 Chengyi Tu , Paolo DOdorico , Zhe Li , Samir Suweis

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

Mean Field Games (MFGs) provide a powerful framework for modeling the collective behavior of large populations of interacting agents. In this paper, we address the problem of Imitation Learning (IL) in MFGs subject to common noise, where…

机器学习 · 计算机科学 2026-05-06 Grégoire Lambrecht , Mathieu Laurière

Subject to reasonable conditions, in large population stochastic dynamics games, where the agents are coupled by the system's mean field (i.e. the state distribution of the generic agent) through their nonlinear dynamics and their nonlinear…

最优化与控制 · 数学 2019-05-28 Nevroz Sen , Peter E. Caines

This paper presents a Mean Field Game (MFG) model for maritime traffic flow, treating the navigation of ships between seaports as a large-scale stochastic control problem. The MFG framework enables the modeling of agents at a microscopic…

最优化与控制 · 数学 2025-12-02 Charles-Albert Lehalle , Giulia Livieri

The mean field limit of large-population symmetric stochastic differential games is derived in a general setting, with and without common noise, on a finite time horizon. Minimal assumptions are imposed on equilibrium strategies, which may…

概率论 · 数学 2014-08-13 Daniel Lacker

Mean-Field Control (MFC) is a powerful tool to solve Multi-Agent Reinforcement Learning (MARL) problems. Recent studies have shown that MFC can well-approximate MARL when the population size is large and the agents are exchangeable.…

机器学习 · 计算机科学 2022-06-02 Washim Uddin Mondal , Vaneet Aggarwal , Satish V. Ukkusuri

Empirically derived continuum models of collective behavior among large populations of dynamic agents are a subject of intense study in several fields, including biology, engineering and finance. We formulate and study a mean-field game…

适应与自组织系统 · 物理学 2018-06-22 Piyush Grover , Kaivalya Bakshi , Evangelos A. Theodorou

The mean field games (MFG) paradigm was introduced to provide tractable approximations of games involving very large populations. The theory typically rests on two key assumptions: homogeneity, meaning that all players share the same…

最优化与控制 · 数学 2025-11-10 Mathieu Laurière

For noncooperative games the mean field (MF) methodology provides decentralized strategies which yield Nash equilibria for large population systems in the asymptotic limit of an infinite (mass) population. The MF control laws use only the…

最优化与控制 · 数学 2012-10-22 Arman C. Kizilkale , Peter E. Caines

We present a method enabling a large number of agents to learn how to flock, which is a natural behavior observed in large populations of animals. This problem has drawn a lot of interest but requires many structural assumptions and is…

多智能体系统 · 计算机科学 2021-05-18 Sarah Perrin , Mathieu Laurière , Julien Pérolat , Matthieu Geist , Romuald Élie , Olivier Pietquin

This paper studies the n-player game and the mean field game under the CRRA relative performance on terminal wealth, in which the interaction occurs by peer competition. In the model with n agents, the price dynamics of underlying risky…

数理金融 · 定量金融 2023-02-10 Lijun Bo , Shihua Wang , Xiang Yu

In this paper we formulate the now classical problem of optimal liquidation (or optimal trading) inside a Mean Field Game (MFG). This is a noticeable change since usually mathematical frameworks focus on one large trader in front of a…

交易与市场微观结构 · 定量金融 2017-09-22 Pierre Cardaliaguet , Charles-Albert Lehalle

We study a general class of entropy-regularized multi-variate LQG mean field games (MFGs) in continuous time with $K$ distinct sub-population of agents. We extend the notion of actions to action distributions (exploratory actions), and…

最优化与控制 · 数学 2021-12-01 Dena Firoozi , Sebastian Jaimungal

In many stochastic games stemming from financial models, the environment evolves with latent factors and there may be common noise across agents' states. Two classic examples are: (i) multi-agent trading on electronic exchanges, and (ii)…

最优化与控制 · 数学 2019-07-24 Dena Firoozi , Peter E. Caines , Sebastian Jaimungal

This thesis is going to give a gentle introduction to Mean Field Games. It aims to produce a coherent text beginning for simple notions of deterministic control theory progressively to current Mean Field Games theory. The framework…

最优化与控制 · 数学 2019-07-03 Athanasios Vasiliadis

In this paper, we present a model of a game among teams. Each team consists of a homogeneous population of agents. Agents within a team are cooperative while the teams compete with other teams. The dynamics and the costs are coupled through…

计算机科学与博弈论 · 计算机科学 2023-10-20 Jayakumar Subramanian , Akshat Kumar , Aditya Mahajan