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 announced in the lecture.
.University of Bonn, Institute for Computer Science, Computer Science VI - Intelligent Systems and Robotics Impress Data Privacy Statement