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Course6.23115 lectures

Dynamic Programming and Stochastic Control

Prof. Dimitri Bertsekas · Massachusetts Institute of Technology

Start with lecture 1 At MIT OpenCourseWare

About

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.

Lectures

Related Video Lectures

  1. Approximate Dynamic Programming, Lecture 1, Part 1 YouTube
  2. Approximate Dynamic Programming, Lecture 1, Part 2 YouTube
  3. Approximate Dynamic Programming, Lecture 1, Part 3 YouTube
  4. Approximate Dynamic Programming, Lecture 2, Part 1 YouTube
  5. Approximate Dynamic Programming, Lecture 2, Part 2 YouTube
  6. Approximate Dynamic Programming, Lecture 2, Part 3 YouTube
  7. Approximate Dynamic Programming, Lecture 3, Part 1 YouTube
  8. Approximate Dynamic Programming, Lecture 3, Part 2 YouTube
  9. Approximate Dynamic Programming, Lecture 4, Part 1 YouTube
  10. Approximate Dynamic Programming, Lecture 4, Part 2 YouTube
  11. Approximate Dynamic Programming, Lecture 5, Part 1 YouTube
  12. Approximate Dynamic Programming, Lecture 5, Part 2 YouTube
  13. Approximate Dynamic Programming, Lecture 5, Part 3 YouTube
  14. Approximate Dynamic Programming, Lecture 6, Part 1 YouTube
  15. Approximate Dynamic Programming, Lecture 6, Part 2 YouTube

Syllabus and materials

At MIT OpenCourseWare, as the course publishes them.

Credits and licence

Institution
Massachusetts Institute of Technology
Department
Electrical Engineering and Computer Science
Teacher
Prof. Dimitri Bertsekas
Term
Fall 2015
Level
Graduate
Language
English
Subjects
Mathematics, Computer science, Engineering
Source
MIT OpenCourseWare
Licence
CC BY-NC-SA 4.0, as MIT OpenCourseWare states it. Non-commercial use only. MIT OpenCourseWare's terms
Attribution
Prof. Dimitri Bertsekas. Dynamic Programming and Stochastic Control. Fall 2015. Massachusetts Institute of Technology: MIT OpenCourseWare, https://ocw.mit.edu/. License: Creative Commons BY-NC-SA.
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