Reinforcement Learning
Contents
In this course, we teach the fundamentals of Reinforcement Learning.
Time and Location
- Lecture: Monday, 10:15 to 11:45, C 014 Hörsaal (A 5, 6 Bauteil C) Dates: Sep 2, 2024 – Dec 2, 2024
- Exercise: Monday, 12:00 to 13:30, D 007 Seminarraum 2 (B 6, 27–29 Bauteil D) Dates: Sep 2, 2024 – Dec 2, 2024
Instructor
Final mark
- Exam (oral)
Participation
- The course is open to students of the Master Business Informatics and Mannheim Master in Data Science (MMDS).
- The course is restricted to 30 participants.
- Places are assigned on first come/
first serve basis. - Students register for the course by email to me (keuper@uni...).
Requirements
- Basics in linear algebra are beneficial for the lecture
Literature
- Richard S. Sutton, Andrew G. Barto, 'Reinforcement Learning: An Introduction' Second Edition MIT Press, Cambridge, MA, 2018
- David Silver, UCL Course on Reinforcement Learning, 2015
- I. Goodfellow et al.: Deep Learning, MIT Press, 2016. (Online: www.deeplearningbook.org)