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401-3909-00L 6 Credits
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Markov Decision Processes and Valuation of Real Options

Lecturers & Examiners: Dr. Juri Hinz
VVZ CR n/a

Last Updated: 2026-02-05 14:59:47

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)
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
  • Tue 13:15-15:00 (HG D 5.2)
2 h weekly
exercise Markov Decision Processes and Valuation of Real Options
  • Mon 15:15-17:00 (HG D 7.2)
1 h weekly

Offered In