This is an archived course. A more recent version may be available at ocw.mit.edu.
Prof. Dimitri Bertsekas
The course covers the basic models and solution techniques for problems of sequential decision making under uncertainty (stochastic control). We will consider optimal control of a dynamical system over both a finite and an infinite number of stages. This includes systems with finite or infinite state spaces, as well as perfectly or imperfectly observed systems. We will also discuss approximation methods for problems involving large state spaces. Applications of dynamic programming in a variety of fields will be covered in recitations.
OCW has published multiple versions of this subject.
Dimitri Bertsekas. 6.231 Dynamic Programming and Stochastic Control, Fall 2011. (Massachusetts Institute of Technology: MIT OpenCourseWare), https://ocw.mit.edu (Accessed). License: Creative Commons BY-NC-SA