Learning Goals: Participants will research the relevant literature on Reinforcement Learning, more specifically on topics related to safety and control. Each student will present one state-of-the-art paper of their choice and apply the method in a coding project. Students will submit a scientific blog at the end of the course. Further information at http://www.ni.tu-belrin.de
Required skills include: Literature research and presentation of researched articles; Students should already be familiar with artificial intelligence (comparable to the topics covered in Machine Intelligence I + II); Programming skills (e.g., python, pytorch, github).
Type of exam: Portfolio
Test elements: Literature review (20%) + Coding (50%) + Presentation (30%)
- Trainer/in: Camilla Groiß