Reinforcement learning

author: Scott Sanner, NICTA
published: April 1, 2009,   recorded: January 2009,   views: 14637


Related Open Educational Resources

Related content

Report a problem or upload files

If you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
Lecture popularity: You need to login to cast your vote.

 Watch videos:   (click on thumbnail to launch)

Watch Part 1
Part 1 57:05
Watch Part 2
Part 2 57:45
Watch Part 3
Part 3 51:48
Watch Part 4
Part 4 55:55
Watch Part 5
Part 5 44:39
Watch Part 6
Part 6 42:45


This course covers the theory and application of reinforcement learning: the task of learning to make optimal sequential decisions when given a delayed reward signal. Topics will include planning in known and unknown environments and will place equal emphasis on theoretical results and practical implementation issues in the context of various applications.

See Also:

Download slides icon Download slides: ssll09_sanner_rele.pdf (3.2┬áMB)

Help icon Streaming Video Help

Link this page

Would you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !

Write your own review or comment:

make sure you have javascript enabled or clear this field: