Research

Our group's research focus is on enabling machines to learn through interactions and become competent in complex, dynamic, and uncertain environments.  To that end, we work on deep reinforcement learning. Our current topics of study within deep reinforcement learning include model-based reinforcement learning, discovering what to learn, leveraging external knowledge sources, LLMs and foundation models, off-policy learning, transfer learning, and meta-learning.