4 papers
CARoL: Context-aware Adaptation for Robot Learning
Zechen Hu, Tong Xu, Xuesu Xiao +1
Using Reinforcement Learning (RL) to learn new robotic tasks from scratch is often inefficient. Leveraging prior knowledge has the potential to significantly enhance learning effic…
Learning Coordinated Maneuver in Adversarial Environments
Zechen Hu, Manshi Limbu, Daigo Shishika +2
This paper aims to solve the coordination of a team of robots traversing a route in the presence of adversaries with random positions. Our goal is to minimize the overall cost of t…
Scaling Team Coordination on Graphs with Reinforcement Learning
Manshi Limbu, Zechen Hu, Xuan Wang +2
This paper studies Reinforcement Learning (RL) techniques to enable team coordination behaviors in graph environments with support actions among teammates to reduce the costs of tr…
Team Coordination on Graphs with State-Dependent Edge Cost
Sara Oughourli, Manshi Limbu, Zechen Hu +3
This paper studies a team coordination problem in a graph environment. Specifically, we incorporate "support" action which an agent can take to reduce the cost for its teammate to…