Project course, 4 hours per week.
Lecturer: Søren Glud Johansen
Content: A short presentation of Renewal Theory and Markov Chains will form the first lectures of the course. Then follows a thorough presentation of the theory about Markov Decision Processes, including different examples of its use. Further examples of the theory and its use will be discussed, based on reports made by the students.
Prerequisites: Computer Science, Mathematical Programming and Probability Theory 1 and Probability theory 2. It is acceptable to follow Probability theory 2 simultaneously with Markov decision theory.
Assessment: A written report which is also presented orally. This report can be accepted as a bachelor project and will then be assessed according to the 13 scale.
Literature: H.C. Tijms: Stochastic Models: An Algorithmic Approach. John Wiley & Sons 1994 (Chapters 1, 2 and 3). S.M. Ross: Introduction to Stochastic Dynamic Programming. Academic Press, 1983 (Chapters 2, 3, 4 and 5). Various articles and technical reports.
ECTS-credits
10.
Semester
Spring 2002.