1 citations · 1 across the 2 of their papers we have counts for
5 papers
Safe adaptation in multiagent competition
Macheng Shen, Jonathan P. How
Achieving the capability of adapting to ever-changing environments is a critical step towards building fully autonomous robots that operate safely in complicated scenarios. In mult…
Scaling Up Multiagent Reinforcement Learning for Robotic Systems: Learn an Adaptive Sparse Communication Graph
Chuangchuang Sun, Macheng Shen, Jonathan P. How
The complexity of multiagent reinforcement learning (MARL) in multiagent systems increases exponentially with respect to the agent number. This scalability issue prevents MARL from…
Robust Opponent Modeling via Adversarial Ensemble Reinforcement Learning in Asymmetric Imperfect-Information Games
Macheng Shen, Jonathan P. How
This paper presents an algorithmic framework for learning robust policies in asymmetric imperfect-information games, where the joint reward could depend on the uncertain opponent t…
Active Perception in Adversarial Scenarios using Maximum Entropy Deep Reinforcement Learning
Macheng Shen, Jonathan P How
We pose an active perception problem where an autonomous agent actively interacts with a second agent with potentially adversarial behaviors. Given the uncertainty in the intent of…
Transferable Pedestrian Motion Prediction Models at Intersections
Macheng Shen, Golnaz Habibi, Jonathan P. How
One desirable capability of autonomous cars is to accurately predict the pedestrian motion near intersections for safe and efficient trajectory planning. We are interested in devel…