30 citations · 106 across the 23 of their papers we have counts for
5 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…
Revisiting Client Puzzles for State Exhaustion Attacks Resilience
Mohammad A. Noureddine, Ahmed Fawaz, Tamer Basar +1
In this paper, we address the challenges facing the adoption of client puzzles as means to protect the TCP connection establishment channel from state exhaustion DDoS attacks. We m…
Resilient Synchronization of Distributed Multi-agent Systems under Attacks
Aquib Mustafa, Rohollah Moghadam, Hamidreza Modares
In this paper, we first address adverse effects of cyber-physical attacks on distributed synchronization of multi-agent systems, by providing conditions under which an attacker can…
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.…