Seminar Advanced Topics in Reinforcement Learning and Decision Making
This will cover current research in the area of learning and decision making. Students will give a presentation of their own research and selected published articles, as well as discuss the presentation given by the other participants. Topics covered include:
- Reinforcement learning
- Learning theory
- Game theory
- Economics and computation
- Fairness in machine learning
Details
| Code | 42597 62597 |
| Type | Seminar |
| ECTS | 5 |
| Site | Neuchâtel |
| Track(s) |
T4 – Theory and Logic T6 – Data Science |
| Semester | S2025 |
Teaching
| Learning Outcomes | The seminar will mainly be student presentations of suggested papers in different sub areas of learning theory, after a suitable brief introduction by the lecturer. The students will be able to critically read scientific articles in each area of decision and learning theory. They will be able to initiate discussion of those papers and communicate the results and main ideas to other scientists in this area. The participants are expected to be able to understand and explain classic papers in the area, as well as present novel ideas contained in recent research either in other authors’ work or in their own, and be able to describe open problems. |
| Lecturer(s) |
Christos Dimitrakakis |
| Language | english |
| Course Page | The course page in ILIAS can be found at https://ilias.unibe.ch/goto_ilias3_unibe_crs_3102281.html. |
Schedules and Rooms
| Period | On Appointment |
| Location | UniNE, Unimail |
Evaluation
| Evaluation type | continuous evaluation |
Additional information
| Comment | First Lecture
|