In the context of robotics and automation, learning from demonstration (LfD) is the paradigm
in which robots acquire new skills by learning to imitate an expert. The choice of LfD over …

Reinforcement Learning is an area of Machine Learning focused on how agents can be
trained to make sequential decisions, and achieve a particular goal within an arbitrary …

Collaborating with humans requires rapidly adapting to their individual strengths,
weaknesses, and preferences. Unfortunately, most standard multi-agent reinforcement …

There has been significant interest of late in generating behavior of agents that is
interpretable to the human (observer) in the loop. However, the work in this area has …

Human behavior prediction models enable robots to anticipate how humans may react to
their actions, and hence are instrumental to devising safe and proactive robot planning …

Human models play a crucial role in human-robot interaction (HRI), enabling robots to
consider the impact of their actions on people and plan their behavior accordingly. However …

As AI systems are integrated into high stakes social domains, researchers now examine how
to design and operate them in a safe and ethical manner. However, the criteria for identifying …

Theory of Mind (ToM)-the ability of the human mind to attribute mental states to others-is a
key component of human cognition. In order to understand other people's mental states or …

Reward functions are a common way to specify the objective of a robot. As designing reward
functions can be extremely challenging, a more promising approach is to directly learn …

We initiate the study of $\textit {behavioral information design} $ through deep learning. In
information design, a $\textit {sender} $ aims to persuade a $\textit {receiver} $ to take certain …