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The course covers the basic models and solution techniques for problems of sequential decision making under uncertainty (stochastic control). This course will consider optimal control of a dynamical system over both a finite and an infinite number of stages and approximation methods for problems involving large state spaces. This includes systems with finite or infinite state spaces, and perfectly or imperfectly observed systems.

Assessment

This course does not involve any written exams. Students need to answer 5 assignment questions to complete the course, the answers will be in the form of written work in pdf or word. Students can write the answers in their own time. Each answer needs to be 200 words (1 Page). Once the answers are submitted, the tutor will check and assess the work.

Certification

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Course Credit: MIT

Course Curriculum

Module 01
Lecture 1 00:15:00
Lecture 2 00:15:00
Lecture 3 00:20:00
Lecture 4 00:20:00
Lecture 5 00:20:00
Lecture 6 00:20:00
Lecture 7 00:20:00
Lecture 8 00:25:00
Lecture 9 00:25:00
Lecture 10 00:30:00
Lecture 11 00:30:00
Lecture 12 00:20:00
Module 02
Lecture 13 00:20:00
Lecture 14 00:25:00
Lecture 15 00:20:00
Lecture 16 00:15:00
Lecture 17 00:20:00
Lecture 18 00:25:00
Lecture 19 00:30:00
Lecture 20 00:30:00
Lecture 21 00:20:00
Lecture 22 00:20:00
Lecture 23 00:40:00
Assessment
Submit Your Assignment 00:00:00
Certification 00:00:00

Course Reviews

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