Conditional Remix & Share Permitted
CC BY-NC-SA
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.
- Subject:
- Applied Science
- Career and Technical Education
- Computer Science
- Electronic Technology
- Engineering
- Mathematics
- Statistics and Probability
- Material Type:
- Full Course
- Provider:
- MIT
- Provider Set:
- MIT OpenCourseWare
- Author:
- Bertsekas, Dimitri
- Date Added:
- 09/01/2015