124 citations · 953 across the 47 of their papers we have counts for
5 papers · 1 filter
Global Convergence of Policy Gradient for Linear-Quadratic Mean-Field Control/Game in Continuous Time
Weichen Wang, Jiequn Han, Zhuoran Yang +1
Reinforcement learning is a powerful tool to learn the optimal policy of possibly multiple agents by interacting with the environment. As the number of agents grow to be very large…
A Two-Timescale Framework for Bilevel Optimization: Complexity Analysis and Application to Actor-Critic
Mingyi Hong, Hoi-To Wai, Zhaoran Wang +1
This paper analyzes a two-timescale stochastic algorithm framework for bilevel optimization. Bilevel optimization is a class of problems which exhibit a two-level structure, and it…
Actor-Critic Provably Finds Nash Equilibria of Linear-Quadratic Mean-Field Games
Zuyue Fu, Zhuoran Yang, Yongxin Chen +1
We study discrete-time mean-field Markov games with infinite numbers of agents where each agent aims to minimize its ergodic cost. We consider the setting where the agents have ide…
Fast Multi-Agent Temporal-Difference Learning via Homotopy Stochastic Primal-Dual Optimization
Dongsheng Ding, Xiaohan Wei, Zhuoran Yang +2
We study the policy evaluation problem in multi-agent reinforcement learning where a group of agents, with jointly observed states and private local actions and rewards, collaborat…
NESTT: A Nonconvex Primal-Dual Splitting Method for Distributed and Stochastic Optimization
Davood Hajinezhad, Mingyi Hong, Tuo Zhao +1
We study a stochastic and distributed algorithm for nonconvex problems whose objective consists of a sum of nonconvex -smooth functions, plus a nonsmooth regularizer. Th…