327 citations · 970 across the 56 of their papers we have counts for
6 papers · 1 filter
Communication-Efficient Policy Gradient Methods for Distributed Reinforcement Learning
Tianyi Chen, Kaiqing Zhang, Georgios B. Giannakis +1
This paper deals with distributed policy optimization in reinforcement learning, which involves a central controller and a group of learners. In particular, two typical settings en…
Finite-Sample Analysis For Decentralized Batch Multi-Agent Reinforcement Learning With Networked Agents
Kaiqing Zhang, Zhuoran Yang, Han Liu +2
Despite the increasing interest in multi-agent reinforcement learning (MARL) in multiple communities, understanding its theoretical foundation has long been recognized as a challen…
Distributed Learning of Average Belief Over Networks Using Sequential Observations
Kaiqing Zhang, Yang Liu, Ji Liu +2
This paper addresses the problem of distributed learning of average belief with sequential observations, in which a network of agents aim to reach a consensus on the average…
Dynamic Power Distribution System Management With a Locally Connected Communication Network
Kaiqing Zhang, Wei Shi, Hao Zhu +2
Coordinated optimization and control of distribution-level assets can enable a reliable and optimal integration of massive amount of distributed energy resources (DERs) and facilit…
Distributed Equilibrium-Learning for Power Network Voltage Control With a Locally Connected Communication Network
Kaiqing Zhang, Wei Shi, Hao Zhu +1
In current power distribution systems, one of the most challenging operation tasks is to coordinate the network- wide distributed energy resources (DERs) to maintain the stability…
Fully Decentralized Multi-Agent Reinforcement Learning with Networked Agents
Kaiqing Zhang, Zhuoran Yang, Han Liu +2
We consider the problem of \emph{fully decentralized} multi-agent reinforcement learning (MARL), where the agents are located at the nodes of a time-varying communication network.…