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Dynamic Programming and Stochastic Control
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6.231 Dynamic Programming and Stochastic Control
As taught in:
Fall 2008
Level:
Graduate
Instructors:
Prof. Dimitri Bertsekas
Course Features
Course Highlights
Course Description
Label correcting methods for shortest paths. See lecture 4 for more information. (Figure by MIT OpenCourseWare, adapted from course notes by Prof. Dimitri Bertsekas.)
Course Features
Lecture notes
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Exams and Solutions
Course Highlights
This course features a complete set of
lecture notes
, as well as
assignments
and
exams
with solutions.
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.