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


Code 62514
Type Seminar
Site Neuchâtel
Track(s) T6 – Data Science
Semester S2023


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

Schedules and Rooms

Period Weekly
Schedule Tuesday, 14:15 - 16:00
Location UniNE, Unimail
Room E213


Evaluation type continuous evaluation

Additional information


First Lecture
The first lecture will be announced later.