Model-Based RL for Mean-Field Games is not Statistically Harder than Single-Agent RL

8 February 2024

Papers citing "Model-Based RL for Mean-Field Games is not Statistically Harder than Single-Agent RL"

10 / 10 papers shown

Title
Steering No-Regret Agents in MFGs under Model Uncertainty Leo Widmer Jiawei Huang Niao He LLMSV 61 0 0 12 Mar 2025
Learning to Steer Markovian Agents under Model Uncertainty Jiawei Huang Vinzenz Thoma Zebang Shen H. Nax Niao He 40 2 0 14 Jul 2024
Learning Regularized Monotone Graphon Mean-Field Games Fengzhuo Zhang Vincent Y. F. Tan Zhaoran Wang Zhuoran Yang 48 7 0 12 Oct 2023
Networked Communication for Decentralised Agents in Mean-Field Games Patrick Benjamin Alessandro Abate FedML 40 2 0 05 Jun 2023
On the Complexity of Multi-Agent Decision Making: From Learning in Games to Partial Monitoring Dylan J. Foster Dean Phillips Foster Noah Golowich Alexander Rakhlin 43 14 0 01 May 2023
Policy Mirror Ascent for Efficient and Independent Learning in Mean Field Games Batuhan Yardim Semih Cayci M. Geist Niao He 53 27 0 29 Dec 2022
A General Framework for Sample-Efficient Function Approximation in Reinforcement Learning Zixiang Chen C. J. Li An Yuan Quanquan Gu Michael I. Jordan OffRL 108 26 0 30 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 58 45 0 28 Feb 2021
Model-free Representation Learning and Exploration in Low-rank MDPs Aditya Modi Jinglin Chen A. Krishnamurthy Nan Jiang Alekh Agarwal OffRL 102 78 0 14 Feb 2021
Approximately Solving Mean Field Games via Entropy-Regularized Deep Reinforcement Learning Kai Cui Heinz Koeppl 64 91 0 02 Feb 2021