2 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.MA2022
DistSPECTRL: Distributing Specifications in Multi-Agent Reinforcement Learning Systems
Joe Eappen, Suresh Jagannathan
While notable progress has been made in specifying and learning objectives for general cyber-physical systems, applying these methods to distributed multi-agent systems still pose…
cs.LG2022★ 2 cited
Defending Observation Attacks in Deep Reinforcement Learning via Detection and Denoising
Zikang Xiong, Joe Eappen, He Zhu +1
Neural network policies trained using Deep Reinforcement Learning (DRL) are well-known to be susceptible to adversarial attacks. In this paper, we consider attacks manifesting as p…
cs.RO2022
Model-free Neural Lyapunov Control for Safe Robot Navigation
Zikang Xiong, Joe Eappen, Ahmed H. Qureshi +1
Model-free Deep Reinforcement Learning (DRL) controllers have demonstrated promising results on various challenging non-linear control tasks. While a model-free DRL algorithm can s…