Distributed Intelligence / Autonomous Learning, Department of Computer Science, University of Tübingen
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.
Highlights
Our Research
Model-based and model-free reinforcement learning, intrinsic motivation, representation learning, combinatorial optimization, haptic sensing, and machine learning for science.
Our Publications
All our papers, searchable and sorted by year.
Our Team
PhD students, postdocs, and researchers in Tübingen and Zürich.
Latest News
Welcome to the new website of the Autonomous Learning Group! Here you will find our research projects, all our publications, and news from the group. Teaching and open positions remain on the university website.
Funding and Sponsors
