Seminar: Advanced Topics in Reinforcement Learning and Planning
Type of course: Seminar
- Master Computer Science
- Master Data Science
- Master Software Systems Engineering
Description: Students will present papers from a list of important, recent works in machine learning compiled by the professor. Topics include deep and reinforcement learning, and transformer and GNN architectures. The focus will be on the use of these techniques in simple applications that are crisp and easy to understand. The list of papers will also include those underlying well-known learning systems like ChaptGPT, AlphaZero, Gato, etc. The final list of papers and topics to be covered will be defined after the first meeting.
Recommended prior knowledge: Bachelor degree in CS or equivalent. Basic AI and ML courses.