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

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)