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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…

Computer Science and Game Theory · Computer Science 2025-07-29 Kai Shao , Jiacheng Shen , Mathieu Laurière

This paper studies multidimensional mean field games with common noise and the related system of McKean-Vlasov forward-backward stochastic differential equations deriving from the stochastic maximum principle. We first propose some…

Probability · Mathematics 2022-12-26 Jodi Dianetti

Mean field type models describing the limiting behavior of stochastic differential games as the number of players tends to +$\infty$, have been recently introduced by J-M. Lasry and P-L. Lions. Under suitable assumptions, they lead to a…

Numerical Analysis · Computer Science 2015-04-23 Yves Achdou , Alessio Porretta

In this paper, we study the multi-dimensional mean-field backward stochastic differential equations (BSDEs, for short) with quadratic growth. Under small terminal value, the existence and uniqueness are proved for the multi-dimensional…

Probability · Mathematics 2022-08-15 Tao Hao , Jiaqiang Wen , Jie Xiong

We study mean field portfolio games under Epstein-Zin preferences, which naturally encompass the classical time-additive power utility as a special case. In a general non-Markovian framework, we establish a uniqueness result by proving a…

Mathematical Finance · Quantitative Finance 2025-05-13 Guanxing Fu , Ulrich Horst

Mean field games are concerned with the limit of large-population stochastic differential games where the agents interact through their empirical distribution. In the classical setting, the number of players is large but fixed throughout…

Optimization and Control · Mathematics 2019-12-30 Julien Claisse , Zhenjie Ren , Xiaolu Tan

In this paper, we study the linear-quadratic control problem for mean-field backward stochastic differential equations (MF-BSDE) with random coefficients. We first derive a preliminary stochastic maximum principle to analyze the unique…

Optimization and Control · Mathematics 2025-03-04 Jie Xiong , Wen Xu , Ying Yang

This work establishes the equivalence between Mean Field Game and a class of PDE systems closely related to compressible Navier-Stokes equations. The solvability of the PDE system via the existence of the Nash Equilibrium of the Mean Field…

Analysis of PDEs · Mathematics 2022-06-28 Tao Luo , Qingshuo Song

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…

Probability · Mathematics 2018-02-01 Alekos Cecchin , Markus Fischer

We derive a priori error estimates for semidiscrete finite element approximations of stable solutions to time-dependent mean field game systems with Dirichlet boundary conditions. Expressing solutions to the MFG system as zeros of a…

Numerical Analysis · Mathematics 2025-11-18 Jules Berry

This paper introduces a new method to achieve stable convergence to Nash equilibrium in duopoly noncooperative games. Inspired by the recent fixed-time Nash Equilibrium seeking (NES) as well as prescribed-time extremum seeking (ES) and…

Optimization and Control · Mathematics 2024-05-27 Victor Hugo Pereira Rodrigues , Tiago Roux Oliveira , Miroslav Krstić , Tamer Başar

This paper studies the convergence of mean field games with finite state space to mean field games with a continuous state space. We examine a space discretization of a diffusive dynamics, which is reminiscent of the Markov chain…

Optimization and Control · Mathematics 2024-01-18 Charles Bertucci , Alekos Cecchin

In this paper we present a scalable deep learning framework for finding Markovian Nash Equilibria in multi-agent stochastic games using fictitious play. The motivation is inspired by theoretical analysis of Forward Backward Stochastic…

Artificial Intelligence · Computer Science 2021-05-24 Tianrong Chen , Ziyi Wang , Ioannis Exarchos , Evangelos A. Theodorou

In this paper, we consider a mean field game (MFG) with a major and $N$ minor agents. We first consider the limiting problem and allow the coefficients to vary with the conditional distribution in a nonlinear way. We use the stochastic…

Optimization and Control · Mathematics 2024-11-05 Ziyu Huang , Shanjian Tang

This paper continues the study of the mean field game (MFG) convergence problem: In what sense do the Nash equilibria of $n$-player stochastic differential games converge to the mean field game as $n\rightarrow\infty$? Previous work on this…

Probability · Mathematics 2018-08-09 Daniel Lacker

This paper is concerned with a class of mean-field type coupled forward-backward stochastic differential equations (MF-FBSDEs, for short), in which the coupling appears in integral terms, terminal terms, and initial terms. Inspired by…

Optimization and Control · Mathematics 2022-03-29 Ran Tian , Zhiyong Yu

In this paper we study a class of matrix-valued linear-quadratic mean-field-type games for both the risk-neutral, risk-sensitive and robust cases. Non-cooperation, full cooperation and adversarial between teams are treated. We provide a…

Optimization and Control · Mathematics 2019-06-06 Julian Barreiro-Gomez , Tyrone E. Duncan , Hamidou Tembine

In this paper, we analyze the mean field backward stochastic differential equations (MFBSDEs) with double mean reflections, whose generator and constraints both depend on the distribution of the solution. When the generator is Lipschitz…

Probability · Mathematics 2026-01-12 Hanwu Li , Jin Shi

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…

Probability · Mathematics 2022-01-19 Luciano Campi , Tiziano De Angelis , Maddalena Ghio , Giulia Livieri

We discuss an open-loop backward Stackelberg differential game involving single leader and single follower. Unlike most Stackelberg game literature, the state to be controlled is characterized by a backward stochastic differential equation…

Optimization and Control · Mathematics 2021-04-06 Xinwei Feng , Ying Hu , Jianhui Huang