Mobile applications can be enhanced through dynamic optimization methods which can be either discrete or in continuous time. Using these methods can only be applied if you have an understanding on the perspectives of dynamic programming and optimal control.
Learning that there are methods that can improve the performance of applications will be emphasized in this Dynamic Optimization Methods with Applications. You will understand the dynamic systems formulated to gain a command of the tools used for optimization.
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 need to be 200 words (1 Page). Once the answers are submitted, the tutor will check and assess the work.
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Course Credit: MIT
|L-1 Vector spaces||00:20:00|
|L-2 The principle of optimality||00:20:00|
|L-3 Concavity and differentiability of the value function||00:15:00|
|L-4 Euler equations||00:10:00|
|L-5 Deterministic dynamics||00:20:00|
|L-6 Models with constant returns to scale||00:20:00|
|L-7 Nonstationary models||00:15:00|
|L-8 Stochastic dynamic programming||00:15:00|
|L-9 Stochastic Euler equations||00:20:00|
|L-10 Discounted infinite-horizon optimal control||00:25:00|
|Submit Your Assignment||00:00:00|
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