37 citations · 49 across the 2 of their papers we have counts for
2 papers
cs.LG2023★ 12 cited
Robustness Testing for Multi-Agent Reinforcement Learning: State Perturbations on Critical Agents
Ziyuan Zhou, Guanjun Liu
Multi-Agent Reinforcement Learning (MARL) has been widely applied in many fields such as smart traffic and unmanned aerial vehicles. However, most MARL algorithms are vulnerable to…
cs.LG2022★ 37 cited
RoMFAC: A robust mean-field actor-critic reinforcement learning against adversarial perturbations on states
Ziyuan Zhou, Guanjun Liu
Multi-agent deep reinforcement learning makes optimal decisions dependent on system states observed by agents, but any uncertainty on the observations may mislead agents to take wr…