Engineering Interactive Learning in Artificial Systems
We look to develop machines that learn through autonomous exploration of and interaction with their environments -- as humans learn. To do this, we use deep reinforcement learning and employ and develop techniques in curiosity, active learning, and self-supervised learning. In doing so, we hope to create artificial systems that can learn more autonomously, flexibly, and robustly, with less demand on data.