Search a title or topic

Over 20 million podcasts, powered by 

Player FM logo
Artwork

Content provided by Richard M. Golden, M.S.E.E., and B.S.E.E.. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Richard M. Golden, M.S.E.E., and B.S.E.E. or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://staging.podcastplayer.com/legal.
Player FM - Podcast App
Go offline with the Player FM app!

LM101-062: How to Transform a Supervised Learning Machine into a Value Function Reinforcement Learning Machine

31:05
 
Share
 

Manage episode 230297540 series 2497400
Content provided by Richard M. Golden, M.S.E.E., and B.S.E.E.. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Richard M. Golden, M.S.E.E., and B.S.E.E. or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://staging.podcastplayer.com/legal.

This 62nd episode of Learning Machines 101 (www.learningmachines101.com) discusses how to design reinforcement learning machines using your knowledge of how to build supervised learning machines! Specifically, we focus on Value Function Reinforcement Learning Machines which estimate the unobservable total penalty associated with an episode when only the beginning of the episode is observable. This estimated Value Function can then be used by the learning machine to select a particular action in a given situation to minimize the total future penalties that will be received. Applications include: building your own robot, building your own automatic aircraft lander, building your own automated stock market trading system, and building your own self-driving car!!

  continue reading

85 episodes

Artwork
iconShare
 
Manage episode 230297540 series 2497400
Content provided by Richard M. Golden, M.S.E.E., and B.S.E.E.. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Richard M. Golden, M.S.E.E., and B.S.E.E. or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://staging.podcastplayer.com/legal.

This 62nd episode of Learning Machines 101 (www.learningmachines101.com) discusses how to design reinforcement learning machines using your knowledge of how to build supervised learning machines! Specifically, we focus on Value Function Reinforcement Learning Machines which estimate the unobservable total penalty associated with an episode when only the beginning of the episode is observable. This estimated Value Function can then be used by the learning machine to select a particular action in a given situation to minimize the total future penalties that will be received. Applications include: building your own robot, building your own automatic aircraft lander, building your own automated stock market trading system, and building your own self-driving car!!

  continue reading

85 episodes

All episodes

×
 
Loading …

Welcome to Player FM!

Player FM is scanning the web for high-quality podcasts for you to enjoy right now. It's the best podcast app and works on Android, iPhone, and the web. Signup to sync subscriptions across devices.

 

Listen to this show while you explore
Play