Dynamic Programming and Stochastic Control
As taught in: Fall 2008
Label correcting methods for shortest paths. See lecture 4 for more information. (Figure by MIT OpenCourseWare, adapted from course notes by Prof. Dimitri Bertsekas.)
Instructors:
Prof. Dimitri Bertsekas
MIT Course Number:
6.231
Level:
Graduate
Course Features
Course Description
This 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 (finite and infinite horizon). We will also discuss some approximation methods for problems involving large state spaces. Applications of dynamic programming in a variety of fields will be covered in recitations.
