Rein4cement Learning

Organisation: Prof. Dr. Verena Wolf, Timo P. Gros.

Topic

Reinforcement Learning is — besides 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 [2].

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 state-of-the-art algorithms of Reinforcement Learning and afterwards apply these to the well-known game Connect 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: the topics presented in the talk and the implementation.

Course page

Find all materials and the registration details here.

References

1. Ahmad Hammoudeh, A Concise Introduction to Reinforcement Learning
2. David Silver, Julian Schrittwieser, Karen Simonyan et al., Mastering the game of Go without human knowledge