94 citations · 99 across the 5 of their papers we have counts for
Showing 2019Show all
2 papers · 1 filter
cs.LG2019★ 2 cited
Monte-Carlo Tree Search for Policy Optimization
Xiaobai Ma, Katherine Driggs-Campbell, Zongzhang Zhang +1
Gradient-based methods are often used for policy optimization in deep reinforcement learning, despite being vulnerable to local optima and saddle points. Although gradient-free met…
cs.LG2019★ 1 cited
Improved Robustness and Safety for Autonomous Vehicle Control with Adversarial Reinforcement Learning
Xiaobai Ma, Katherine Driggs-Campbell, Mykel J. Kochenderfer
To improve efficiency and reduce failures in autonomous vehicles, research has focused on developing robust and safe learning methods that take into account disturbances in the env…