IE 560 Foundations of Artificial Intelligence – Reasoning and Decision Making (HWS 2026)
This course provides a foundational introduction to the principles and methods underlying artificial intelligence, with a focus on reasoning and decision making. The course covers the following topics:
- Logic-based knowledge representation and reasoning
- Probabilistic graphical models for reasoning under uncertainty
- Decision theory and rational decision making
- Markov Decision Processes
- Reinforcement Learning
Dates
Lecture: Inverted classroom consisting of video lectures and a Q&A session every week (Monday, 12:00; Room C014, A5)
Exercise:
- Monday 13:45 – 15:15, A5, C014 or
- Monday 15:30 – 17:00, A5, C013
Assessments
Written examination.
Instructors
Lea Cohausz
Slides and Excercises
See the ILIAS page for slides, dates and further information.
Literature
- S. Russel and P. Norvig: Artificial Intelligence – A modern Approach. Pearson 2013. (selected chapters)
- R. S. Sutton and A. G. Barto: Reinforcement Learning – An Introduction. MIT Press. 2018. (selected chapters)