VVZ API is not affiliated with ETH Zurich. Data might be outdated or incorrect. Please view the official ETHZ Vorlesungsverzeichnis for binding information.
Abstract
Markov decision models represent efficient analytical tools for mathematical description and optimization of sequencial decision schemes, as encountered in many economical and industrial environments. In this lecture such models and the corresponding optimization algorithms are treated.
Content
Markov decision models represent efficient analytical tools for mathematical description and optimization of sequencial decision schemes, as encountered in many economical and industrial environments. In this lecture such models and the corresponding optimization algorithms are treated. Key words: discrete and continuous markov chains, cost structures and optimality criteria, dynamic programming, value iteration and policy iteration, formulation as linear programming Problems, optimal control of semi-markovian processes and markov renewal programming.
General Information
- Language
- English (lecture), German (exercise)
- Levels
- BSC , DS , MSC
- Frequency
- Every two years
Examination
- Type
- session examination
- Mode
- oral 30 minutes
Course Components
| Type | Title | Time & Place | Hours |
|---|---|---|---|
| lecture |
Markov Decision Processes and Valuation of Real Options
Does not take place this semester.
|
No time listed | 2 h weekly |
| exercise |
Markov Decision Processes and Valuation of Real Options
Does not take place this semester.
|
|
1 h weekly |