This lecture is one of the introductory lectures of the
intelligent systems track of
the master programme "Computer Science".
Creating autonomous robots that can learn to assist humans in situations of daily life is a fascinating challenge for machine learning.
The lecture covers key ingredients for a general robot learning approach to get closer towards human-like performance in robotics, such as reinforcement learning, learning models for control, learning motor primitives, learning from demonstrations and imitation learning, and interactive learning.
- R.Sutton and A. Barto: Reinforcement Learning: An Introduction. MIT Press, 1998.
- O. Sigaud and J. Peters (Eds.): From Motor Learning to Interaction Learning in Robots. Springer, 2010.
- Additional literature will be mentioned in the lecture..