31 citations · 65 across the 57 of their papers we have counts for
4 papers · 1 filter
Finite-Sample Analysis of Decentralized Q-Learning for Stochastic Games
Zuguang Gao, Qianqian Ma, Tamer Başar +1
Learning in stochastic games is arguably the most standard and fundamental setting in multi-agent reinforcement learning (MARL). In this paper, we consider decentralized MARL in st…
On Improving Model-Free Algorithms for Decentralized Multi-Agent Reinforcement Learning
Weichao Mao, Lin F. Yang, Kaiqing Zhang +1
Multi-agent reinforcement learning (MARL) algorithms often suffer from an exponential sample complexity dependence on the number of agents, a phenomenon known as \emph{the curse of…
Asynchronous Networked Aggregative Games
Rongping Zhu, Jiaqi Zhang, Keyou You +1
We propose a fully asynchronous networked aggregative game (Asy-NAG) where each player minimizes a cost function that depends on its local action and the aggregate of all players'…
Derivative-Free Policy Optimization for Linear Risk-Sensitive and Robust Control Design: Implicit Regularization and Sample Complexity
Kaiqing Zhang, Xiangyuan Zhang, Bin Hu +1
Direct policy search serves as one of the workhorses in modern reinforcement learning (RL), and its applications in continuous control tasks have recently attracted increasing atte…