Departments' graduate courses
Course start and periodicity may vary. Please see details for each course for up-to-date information. The courses are managed and administered by the respective departments. For more information about the courses, how to sign up, and other practical issues, please contact the examiner or course contact to be found in the course information.
Advanced Topics in Reinforcement Learning and Decision Making
- Course code: FDAT115
- Course higher education credits: 7.5
- Department: COMPUTER SCIENCE AND ENGINEERING
- Graduate school: Computer Science and Engineering
- Course start: 2018-02-12
- Course end: 2018-04-26
- Course is normally given: Next starting date will be decided by interest.
- Language: The course will be given in English
- Nordic Five Tech (N5T): This course is free for PhD students from N5T universities
Each week is a mixture of lectures, discussions of academic papers, and
hands-on work. In the first part of the course, there will be home assignments, for which the
hands-on work prepares them. There are 4 assignments in total, a well as a mini-project (done
in teams of 2-3 students), where students integrate what they have learned.
Advanced students may replace 2 assignments with being discussion leader for a week.
The course mainly follows the structure of our draft book, "Decision Making Under Uncertainty and Reinforcement Learning" (see website). Other material will be referred to in the reading assignments.
Christos Dimitrakakis: email@example.com
Additional lecturers may be invited.