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Finding and transferring policies using stored behaviors

Finding and transferring policies using stored behaviors We present several algorithms that aim to advance the state-of-the-art in reinforcement learning and planning algorithms. One key idea is to transfer knowledge across problems by representing it using local features. This idea is used to speed up a dynamic programming based generalized policy iteration. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Autonomous Robots Springer Journals

Finding and transferring policies using stored behaviors

Autonomous Robots , Volume 29 (2) – May 6, 2010

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References (73)

Publisher
Springer Journals
Copyright
Copyright © 2010 by Springer Science+Business Media, LLC
Subject
Engineering; Computer Imaging, Vision, Pattern Recognition and Graphics; Artificial Intelligence (incl. Robotics); Control , Robotics, Mechatronics; Robotics and Automation
ISSN
0929-5593
eISSN
1573-7527
DOI
10.1007/s10514-010-9191-2
Publisher site
See Article on Publisher Site

Abstract

We present several algorithms that aim to advance the state-of-the-art in reinforcement learning and planning algorithms. One key idea is to transfer knowledge across problems by representing it using local features. This idea is used to speed up a dynamic programming based generalized policy iteration.

Journal

Autonomous RobotsSpringer Journals

Published: May 6, 2010

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