Approximate Dynamic Programming for Stochastic and Dynamic Decision Problems

The 4-day course deals with anticipatory methods for dynamic decision making. It will address the following questions:

  1. What are the components of dynamic decision processes and how do they interact?
  2. How can dynamic decision processes be modeled mathematically?
  3. What is approximate dynamic programming? What methods exist to solve dynamic decision processes? What methods are suitable for what type of problem?

In this course, we describe the process to approach complex stochastic and dynamic decision problems with advanced ADP-methods. We present the required steps from business problem over MDP to the ADP-solutions in detail and give an overview over the most prominent ADP-methods. We especially focus on offline learning methods known as value function approximations. The theoretical content of this course is accompanied by many illustrative examples from the field of logistics and by a serious gaming application.


2019, March, 18-21


Haus der Wissenschaft Braunschweig
Pockelsstraße 11, 5th floor,
38106 Braunschweig

Prof. Dr. Dirk Mattfeld
Universität Braunschweig

Jun.-Prof. Dr. Marlin Ulmer
Universität Braunschweig


To get an overview of the amount of the participation fee and to register for the course, please use this link:

You can also send an email to prodok(at)vhbonline(dot)org. 

Registration Deadline: 3. März 2019