Deep learning has seen significant growth recently and is now applied to a wide range of
conventional use cases, including graphs. Graph data provides relational information …

Abstract Purpose of Review Current real-world interaction between humans and robots is
extremely limited. We present challenges that, if addressed, will enable humans and robots …

Recent advances in machine learning have led to growing interest in Explainable AI (xAI) to
enable humans to gain insight into the decision-making of machine learning models …

In recent years, teams of robot and Unmanned Aerial Vehicles (UAVs) have been
commissioned by researchers to enable accurate, online wildfire coverage and tracking …

High-performing teams learn intelligent and efficient communication and coordination
strategies to maximize their joint utility. These teams implicitly understand the different roles …

Information sharing is key in building team cognition and enables coordination and
cooperation. High-performing human teams also benefit from acting strategically with …

Decision Transformers (DT) have drawn upon the success of Transformers by abstracting
Reinforcement Learning as a target-return-conditioned, sequence modeling problem. In our …

Extending recent advances in Learning from Demonstration (LfD) frameworks to multi-robot
settings poses critical challenges such as environment non-stationarity due to partial …

High-performing human–human teams learn intelligent and efficient communication and
coordination strategies to maximize their joint utility. These teams implicitly understand the …

High-performing human teams leverage intelligent and efficient communication and
coordination strategies to collaboratively maximize their joint utility. Inspired by teaming …