Reinforcement Learning is - beside Supervised and Unsupervised Learning - one of the outstanding variants of Machine Learning. It has evolved to an effective tool, being able to create AI systems that are able to beat humans in almost every game, e.g. the famous strategy board game Go .
This seminar will try to do both: teach the basics of Reinforcement Learning in theory and also provide the ability to apply it. We will therefore first have a look at the actual state of the art algorithms of Reinforcement Learning and afterwards apply these to the well known game Collect 4.
The seminar will include a short talk, a programming project that will be solved in small groups as well as a write-up about both former: the topics presented in the talk and the implementation.
Find all materials and the registation details here
 Ahmad Hammoudeh : A Concise Introduction to Reinforcement Learning
 David Silver, Julian Schrittwieser, Karen Simonyan et al. : Mastering the game of Go without human knowledge