September 01 – 04, 2014 in Leipzig at Max Planck Institute for Mathematics in the Sciences financially supported by the DFG Priority Programme Autonomous Learning(for more information and online tutorials see the Summer School’s website at MPI for Mathematics in the Sciences)
Autonomous Learning research aims at understanding how autonomous systems can efficiently learn from the interaction with the environment, especially by having an integrated approach to decision making and learning, allowing systems to autonomously decide on actions, representations, hyperparameters and model structures for the purpose of efficient learning. In this summer school international and national experts will introduce to the core concepts and related theory for autonomous learning in real-world environments.
We hope to foster the enthusiasm of young researchers for this exciting research area, giving them the opportunity to meet leading experts in the field and similarly interested students. Our school offers an opportunity to look into fundamental and advanced aspects of autonomous learning. The tutorials are structured around three themes:
- learning representations,
- acting to learn (exploration), and
- learning to act in real-world environments (robotics).
Invited external lecturer
Lecturer associated with the DFG Priority Programme Autonomous Learning
- Tamim Asfour (KIT Karlsruhe)
- Michael Beetz (Bremen University)
- Matthias Bethge (University of Tübingen, MPI for Biological Cybernetics, Bernstein Center for Computational Neuroscience)
- Thomas Martinetz (University of Lübeck)
- Helge Ritter (Bielefeld University)
- Friedrich Sommer (Redwood Center for Theoretical Neuroscience, UC Berkeley)
- Marc Toussaint (Stuttgart University)
- Keyan Zahedi (MPI for Mathematics in the Sciences)