Code |
Course Name |
Language |
Type |
VBA 441E |
Reinforcement Learning |
English |
Elective |
Local Credits |
ECTS |
Theoretical |
Tutorial |
Laboratory |
3 |
4 |
3 |
0 |
0 |
Course Prerequisites and Class Restriction |
Prerequisites |
VBA 224E MIN DD
|
Class Restriction |
None |
Course Description |
This course provides an introduction to some of the foundational ideas of reinforcement learning, including
Markov decision processes, value functions, Monte Carlo estimation, dynamic programming, temporal
difference learning, eligibility traces, and function approximation. However, we will also cover additional
material drawn from the latest deep Reinforcement Learning literature. Programming assignments and projects
will require implementing and testing these techniques for various problems. |
|