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Last updated:

August 5, 2022

Duration:

Unlimited Duration

FREE

This course includes:

Unlimited Duration

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Description

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.

Course Curriculum

    • Lecture 1 Unlimited
    • Lecture 2 Unlimited
    • Lecture 3 Unlimited
    • Lecture 4 Unlimited
    • Lecture 5 Unlimited
    • Lecture 6 Unlimited
    • Lecture 7 Unlimited
    • Lecture 8 Unlimited
    • Lecture 9 Unlimited
    • Lecture 10 Unlimited
    • Lecture 11 Unlimited
    • Lecture 12 Unlimited
    • Lecture 13 Unlimited
    • Lecture 14 Unlimited
    • Lecture 15 Unlimited
    • Lecture 16 Unlimited
    • Lecture 17 Unlimited
    • Lecture 18 Unlimited
    • Lecture 19 Unlimited
    • Lecture 20 Unlimited
    • Lecture 21 Unlimited
    • Lecture 22 Unlimited
    • Lecture 23 Unlimited

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Massachusetts Institute of Technology