Distributed Intelligence / Autonomous Learning Group

We are interested in autonomous learning, that is how an embodied agent can determine what to learn, how to learn, and how to judge the learning success. In particular, we focus on learning to control a robotic body in a developmental fashion. Artificial intrinsic motivations are a central component that we develop using information theory and dynamical systems theory. We work on reinforcement learning, representation learning, and internal model learning.