Unified Reinforcement Q-Learning for Mean Field Game and Control
Problems

Unified Reinforcement Q-Learning for Mean Field Game and Control Problems

24 June 2020

Mathieu Laurière

Papers citing "Unified Reinforcement Q-Learning for Mean Field Game and Control Problems"

9 / 9 papers shown

Title
Stochastic Semi-Gradient Descent for Learning Mean Field Games with Population-Aware Function Approximation Chenyu Zhang Xu Chen Xuan Di 81 4 0 17 Feb 2025
Last Iterate Convergence in Monotone Mean Field Games Noboru Isobe Kenshi Abe Kaito Ariu 27 0 0 07 Oct 2024
Independent RL for Cooperative-Competitive Agents: A Mean-Field Perspective Muhammad Aneeq uz Zaman Alec Koppel Mathieu Laurière Tamer Basar 37 3 0 17 Mar 2024
Deep Reinforcement Learning for Infinite Horizon Mean Field Problems in Continuous Spaces Andrea Angiuli J. Fouque Ruimeng Hu Alan Raydan 27 5 0 19 Sep 2023
Networked Communication for Decentralised Agents in Mean-Field Games Patrick Benjamin Alessandro Abate FedML 32 2 0 05 Jun 2023
Mean-Field Control based Approximation of Multi-Agent Reinforcement Learning in Presence of a Non-decomposable Shared Global State Washim Uddin Mondal Vaneet Aggarwal S. Ukkusuri 22 8 0 13 Jan 2023
Graphon Mean-Field Control for Cooperative Multi-Agent Reinforcement Learning Yuanquan Hu Xiaoli Wei Jun Yan Heng-Wei Zhang 26 8 0 11 Sep 2022
Scaling up Mean Field Games with Online Mirror Descent Julien Perolat Sarah Perrin Romuald Elie Mathieu Laurière Georgios Piliouras M. Geist K. Tuyls Olivier Pietquin LRM AI4CE 48 45 0 28 Feb 2021
Thompson sampling for linear quadratic mean-field teams Mukul Gagrani Sagar Sudhakara Aditya Mahajan A. Nayyar Ouyang Yi 11 4 0 09 Nov 2020