• Theoretical background for the design of cyber-physical systems (CPS). Models and algorithms to state estimation, control and planning are introduced.
• Usage of tought paradigms, i.e., implementation of parts of a CPS including an introduction to robotics.
• Supervised learning with Deep Neural Networks.

• Uncertain knowledge and reasoning in embedded systems
• Rational Agents
• Bayes nets representation and independence
• Bayes nets inference
• HMMs, Kalman filters and particle filters
• Decision making
• Learning
• Robotics
• Supervised learning with Deep Neural Networks
• Reinforcement learning with Deep Neural Networks

Didactic concept: Topics are tought in the lectures and practiced in exercises including programming exercises, simulation and application on real-world mobile robots.

Lectures start s.t.

ECTS-Breakdown 3 ECTS = 150 hours:

Lecture part:

• 0.5h  lecture introduction
• 54h (18 lectures, 2h per lecture + 1h pre/postprocessing)
• 20h exam preparation
• 0.5h  oral exam
  ----
  75h

Exercise part:

• 75h exercises

• Oral exam
• Submitted exercises
• Delivery talks of practical exercises

Registration to the course via TISS. You will be added to the TUWEL course, where the rest of the course will be organized.

S. Russel and P. Norvig, Artificial Intelligence - A Modern Approach, 3rd ed., Upper Saddle River, New Jersey: Pearson Education, 2010.