4 citations · 9 across the 3 of their papers we have counts for
3 papers
Regret Bounds for Decentralized Learning in Cooperative Multi-Agent Dynamical Systems
Seyed Mohammad Asghari, Yi Ouyang, Ashutosh Nayyar
Regret analysis is challenging in Multi-Agent Reinforcement Learning (MARL) primarily due to the dynamical environments and the decentralized information among agents. We attempt t…
Learning Latent State Spaces for Planning through Reward Prediction
Aaron Havens, Yi Ouyang, Prabhat Nagarajan +1
Model-based reinforcement learning methods typically learn models for high-dimensional state spaces by aiming to reconstruct and predict the original observations. However, drawing…
Online Learning in Planar Pushing with Combined Prediction Model
Huidong Gao, Yi Ouyang, Masayoshi Tomizuka
Pushing is a useful robotic capability for positioning and reorienting objects. The ability to accurately predict the effect of pushes can enable efficient trajectory planning and…