By Topic

Autonomous Model Learning for Reinforcement Learning

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

1 Author(s)

Stochastic modeling is an excellent way of capturing system dynamics so that alternative control strategies can be evaluated and compared. I will discuss attributes that make some problems amenable to autonomous learning of system dynamics. I will then present recent advances in my lab concerning the design of learning algorithms with formal learning-time guarantees in the "KWIK" (knows what it knows) formalism along with their implementation on robotic and software control problems.

Published in:

Quantitative Evaluation of Systems, 2008. QEST '08. Fifth International Conference on

Date of Conference:

14-17 Sept. 2008