Reinforcement Learning

Reinforcement Learning (Lecture)

• Organized by:
• Prof. Joschka Boedecker and Gabriel Kalweit
• Lecture:
• HISinOne number: 11LE13V-1141
• Language:
• English
• Session:
• Friday 14:00 - 16:00
• Building 082 HS 00 006
• Exam:
• TBA

Overview:

The lecture deals with methods of Reinforcement Learning that constitute an important class of machine learning algorithms. Starting with the formalization of problems as Markov decision processes, a variety of Reinforcement Learning methods are introduced and discussed in-depth. The connection to practice-oriented problems is established throughout the lecture based on many examples.

Format:

The course will be held in a flipped classroom manner. We'll watch a lecture recording at home each week and meet to answer questions, discuss the new content and the exercises. The exercises will not be mandatory. However, there will be a project for which you have to get 50% of the points in order to participate in the final exam.

All lecture recordings, slides and exercises can be found in ILIAS.