327 citations · 970 across the 56 of their papers we have counts for
5 papers · 1 filter
Independent Learning in Stochastic Games
Asuman Ozdaglar, Muhammed O. Sayin, Kaiqing Zhang
Reinforcement learning (RL) has recently achieved tremendous successes in many artificial intelligence applications. Many of the forefront applications of RL involve multiple agent…
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…
Decentralized Q-Learning in Zero-sum Markov Games
Muhammed O. Sayin, Kaiqing Zhang, David S. Leslie +2
We study multi-agent reinforcement learning (MARL) in infinite-horizon discounted zero-sum Markov games. We focus on the practical but challenging setting of decentralized MARL, wh…
Learning Safe Multi-Agent Control with Decentralized Neural Barrier Certificates
Zengyi Qin, Kaiqing Zhang, Yuxiao Chen +2
We study the multi-agent safe control problem where agents should avoid collisions to static obstacles and collisions with each other while reaching their goals. Our core idea is t…
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…