During the this semester I am teaching the course “Markov decision theory” at the Department of Mathematics. The course presents the algorithmic aspects of Markov decision theory and illustrates the wide applicability of this theory to a variety of realistic problems. First, the course consider the Poisson process followed by Renewal/Reward Processes. Next we study the theory of Markov chains. Then follows a thorough presentation of the theory of Markov Decision Processes, including some applications. Finally, further applications are discussed based on reports made by the students. A course plan is given here.
You may also like
R package gMOIP has been updated to version 1.3.0 and now can plot 3D models too. The package can make 2D and […]
Aim of ESI 2009 is to bring together young scientists with academic experts on OR methods besides the development of applications for […]
Often when I teach students at our Business School they have a hard time understanding compact linear programming (LP) formulations. So here […]
Den 16. marts deltog jeg i kursuset “Vejledning af større studenteropgaver – bachelorprojekt og kandidatafhandling”. Det giver et hurtig overblik over hvilke […]