DE
Modul
Markov Decision Processes [M-MATH-102907]
Credits
5Recurrence
UnregelmäßigDuration
1 SemesterLanguage
Level
4Version
1Responsible
Organisation
- KIT-Fakultät für Mathematik
Part of
Bricks
Identifier | Name | LP |
---|---|---|
T-MATH-105921 | Markov Decision Processes | 5 |
Competence Certificate
The module will be completed by an oral exam (about 20 min).
Competence Goal
At the end of the course, students
- can name the mathematical foundations of Markov Decision Processes and apply solution algorithm,
- can formulate stochastic, dynamic optimization problems as Markov Decision Processes,
- are able to work in a self-organized and reflective manner.
Prerequisites
none
Content
-
MDPs with finite time horizon
- Bellman equation
- Problems with structure
- Applications -
MDPs with infinite time horizon
- contracting MDPs
- positive MDPs
- Howards policy improvement
- Solution by linear programs -
Stopping problems
- finite and infinite time horizon
- One-step-look-ahead rule
Recommendation
The course 'Probability theory' is strongly recommended and 'Markov chains' is recommended.
Workload
Total workload: 150 hours
Attendance: 60 hours
- lectures, problem classes, and examination
Self-studies: 90 hours
- follow-up and deepening of the course content,
- work on problem sheets,
- literature study and internet research relating to the course content,
- preparation for the module examination