The Online Discovery Problem and Its Application to Lifelong Reinforcement Learning
published: July 28, 2015, recorded: June 2015, views: 2510
Report a problem or upload filesIf 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.
We study lifelong reinforcement learning where the agent extracts knowledge from solving a sequence of tasks to speed learning in future ones. We first formulate and study a related online discovery problem, which can be of independent interest, and propose an optimal algorithm with matching upper and lower bounds. These results are then applied to create a robust, continuous lifelong reinforcement learning algorithm with formal learning guarantees, applicable to a much wider scenarios, as verified in simulations.
Link this pageWould you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !