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Linear-quadratic optimal control problems are considered for mean-field stochastic differential equations with deterministic coefficients. Time-inconsistency feature of the problems is carefully investigated. Both open-loop and closed-loop…

Optimization and Control · Mathematics 2013-05-07 Jiongmin Yong

We develop a probabilistic approach to continuous-time finite state mean field games. Based on an alternative description of continuous-time Markov chain by means of semimartingale and the weak formulation of stochastic optimal control, our…

Probability · Mathematics 2018-08-24 Rene Carmona , Peiqi Wang

We consider strongly monotone games with convex separable coupling constraints, played by dynamical agents, in a partial-decision information scenario. We start by designing continuous-time fully distributed feedback controllers, based on…

Optimization and Control · Mathematics 2021-05-05 Mattia Bianchi , Sergio Grammatico

The goal of this work is to identify steady-state solutions to dynamical systems defined on large, random families of networks. We do so by passing to a continuum limit where the adjacency matrix is replaced by a non-local operator with…

Dynamical Systems · Mathematics 2026-02-26 Jason J. Bramburger , Matt Holzer , Jackson Williams

Motivated by mean-field games (MFG) with common noise on the one hand and pathwise stochastic control theory on the other, we formulate here a linear-quadratic (LQ) MFG with rough common noise, along with a satisfactory well-posedness…

Probability · Mathematics 2026-04-14 Peter K. Friz , Ioannis Gasteratos , Ulrich Horst , Stefanos Theodorakopoulos

This paper studies a class of partial information linear-quadratic mean-field game problems. A general stochastic large-population system is considered, where the diffusion term of the dynamic of each agent can depend on the state and…

Optimization and Control · Mathematics 2022-03-22 Min Li , Tianyang Nie , Zhen Wu

In a graphical game agents play with their neighbors on a graph to achieve an appropriate state of equilibrium. Here relevant problems are characterizing the equilibrium set and discovering efficient algorithms to find such an equilibrium…

Statistical Mechanics · Physics 2011-09-06 A. Ramezanpour , J. Realpe-Gomez , R. Zecchina

A game-theoretic framework for time-inconsistent stopping problems where the time-inconsistency is due to the consideration of a non-linear function of an expected reward is developed. A class of mixed strategy stopping times that allows…

Optimization and Control · Mathematics 2020-01-23 Sören Christensen , Kristoffer Lindensjö

In this paper, we consider stochastic monotone Nash games where each player's strategy set is characterized by possibly a large number of explicit convex constraint inequalities. Notably, the functional constraints of each player may depend…

Optimization and Control · Mathematics 2023-08-25 Zeinab Alizadeh , Afrooz Jalilzadeh , Farzad Yousefian

In this paper, our goal is to study fundamental foundations of linear quadratic Gaussian (LQG) control problems for stochastic linear time-invariant systems via Lagrangian duality of semidefinite programming (SDP) problems. In particular,…

Optimization and Control · Mathematics 2021-08-21 Donghwan Lee

We address the numerical solution of second-order Mean Field Game problems through Newton iterations in infinite dimensions, introduced in [14], where quadratic convergence of the method was rigorously established. Building upon this…

Numerical Analysis · Mathematics 2026-03-20 Elisabetta Carlini , Ahmad Zorkot

In this paper, we present a sequential decomposition algorithm equivalent of Master equation to compute GMFE of GMFG and graphon optimal Markovian policies (GOMPs) of graphon mean field teams (GMFTs). We consider a large population of…

Computer Science and Game Theory · Computer Science 2022-06-08 Deepanshu Vasal , Rajesh K Mishra , Sriram Vishwanath

In this paper, we study the long-time behavior of mean field game (MFG) systems influenced by a common noise. While classical results establish the convergence of deterministic MFG towards stationary solutions under suitable monotonicity…

Analysis of PDEs · Mathematics 2025-09-23 Pierre Cardaliaguet , Raphaël Maillet , Wenbin Yan

Traditional mean-field game (MFG) solvers operate on an instance-by-instance basis, which becomes infeasible when many related problems must be solved (e.g., for seeking a robust description of the solution under perturbations of the…

Optimization and Control · Mathematics 2025-10-24 Dena Firoozi , Anastasis Kratsios , Xuwei Yang

In this paper we establish quantitative convergence results for both open and closed-loop Nash equilibria of N-player stochastic differential games in the setting of Mean Field Games of Controls (MFGC), a class of models where interactions…

Probability · Mathematics 2025-07-24 Joe Jackson , Alpár R. Mészáros

This paper introduces a framework of Constrained Mean-Field Games (CMFGs), where each agent solves a constrained Markov decision process (CMDP). This formulation captures scenarios in which agents' strategies are subject to feasibility,…

Optimization and Control · Mathematics 2025-10-15 Anran Hu , Zijiu Lyu

This paper is concerned with a new class of mean-field games which involve a finite number of agents. Necessary and sufficient conditions are obtained for the existence of the decentralized open-loop Nash equilibrium in terms of…

Optimization and Control · Mathematics 2022-06-14 Bing-Chang Wang , Huanshui Zhang , Minyue Fu , Yong Liang

Formation control problems can be expressed as linear quadratic discrete-time games (LQDTG) for which Nash equilibrium solutions are sought. However, solving such problems requires solving coupled Riccati equations, which cannot be done in…

Optimization and Control · Mathematics 2023-09-06 Prima Aditya , Herbert Werner

Motivated by the self-pursuit of controlled objects, we consider the exact controllability of a linear mean-field type game-based control system (MF-GBCS, for short) generated by a linear-quadratic (LQ, for short) Nash game. A Gram-type…

Optimization and Control · Mathematics 2023-03-01 Cui Chen , Zhiyong Yu

Mean field games (MFGs) describe the collective behavior of large populations of interacting agents. In this work, we tackle ill-posed inverse problems in potential MFGs, aiming to recover the agents' population, momentum, and environmental…

Machine Learning · Computer Science 2025-02-18 Jingguo Zhang , Xianjin Yang , Chenchen Mou , Chao Zhou