Mediaspace scheduled maintenance: Aug 25, 2026 07:00 - 12:00 AM. During this time, videos will be temporarily unavailable. Check status updates.

Graph
Search

Course

ENG-639: Dynamic programming and optimal control

Summary

This course provides an introduction to stochastic optimal control and dynamic programming (DP), with a variety of engineering applications. The course focuses on the DP principle of optimality, and its utility in deriving and approximating solutions to an optimal control problem.

Lectures

Instructor

Tyler Summers

Official source

https://edu.epfl.ch/coursebook/en/dynamic-programming-and-optimal-control-ENG-639

Moodle Page

http://go.epfl.ch/ENG-639

About this result

This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.

Summary

Lectures

Instructor

Tyler Summers

Official source

https://edu.epfl.ch/coursebook/en/dynamic-programming-and-optimal-control-ENG-639

Moodle Page

http://go.epfl.ch/ENG-639

About this result

Related courses (31)

PHYS-467: Machine learning for physicists

Machine learning and data analysis are becoming increasingly central in sciences including physics. In this course, fundamental principles and methods of machine learning will be introduced and practised. ...

MGT-484: Applied probability & stochastic processes

This course focuses on dynamic models of random phenomena, and in particular, the most popular classes of such models: Markov chains and Markov decision processes. We will also study applications in queuing theory, finance, project management, etc. ...

EE-556: Mathematics of data: from theory to computation

This course provides an overview of key advances in continuous optimization and statistical analysis for machine learning. We review recent learning formulations and models as well as their guarantees

CS-450: Algorithms II

A first graduate course in algorithms, this course assumes minimal background, but moves rapidly. The objective is to learn the main techniques of algorithm analysis and design, while building a repertory of basic algorithmic solutions to problems in many ...

MGT-418: Convex optimization

This course introduces the theory and application of modern convex optimization from an engineering perspective. ...