Reinforcement Learning for Engineers, Part 3: Policies and Learning Algorithms

Check out the other videos in the series:
Part 1 - What Is Reinforcement Learning: https://youtu.be/pc-H4vyg2L4
Part 2 - Understanding the Environment and Rewards: https://youtu.be/0ODB_DvMiDI
Part 3 - Policies and Learning Algorithms: https://youtu.be/7cF3VzP5EDI
Part 4 - The Walking Robot Problem: https://youtu.be/Wypc1a-1ZYA
Part 5 - Overcoming the Practical Challenges: https://youtu.be/zHV3UcH-nr0

This video provides an introduction to the algorithms that reside within the agent. We’ll cover why we use neural networks to represent functions and why you may have to set up two neural networks in a powerful family of methods called actor-critic.

Reinforcement Learning by Sutton and Barto: http://bit.ly/2HAYbb4
Reinforcement Learning Toolbox: https://bit.ly/2YjuAYa
RL course by David Silver: https://youtu.be/2pWv7GOvuf0
3B1B videos on neural networks: http://bit.ly/2WRmaq9
Michael Neilson’s blog: Follow up: http://bit.ly/2WMUtP1
A nice write up on policy gradient algorithms and the policy gradient theorem by Lilian Weng: http://bit.ly/2WP6bIS
A paper motivating the usefulness of deep neural networks: http://bit.ly/2WI591o
Brendan Fortuner’s blog: http://bit.ly/2WUmRyJ
--------------------------------------------------------------------------------------------------------
Get a free product Trial: https://goo.gl/ZHFb5u
Learn more about MATLAB: https://goo.gl/8QV7ZZ
Learn more about Simulink: https://goo.gl/nqnbLe
See What's new in MATLAB and Simulink: https://goo.gl/pgGtod

© 2019 The MathWorks, Inc. MATLAB and Simulink are registered
trademarks of The MathWorks, Inc.
See www.mathworks.com/trademarks for a list of additional trademarks. Other product or brand names may be trademarks or registered trademarks of their respective holders.

Видео Reinforcement Learning for Engineers, Part 3: Policies and Learning Algorithms канала MATLAB