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  Efficient Sample Reuse in EM-Based Policy Search

Hachiya, H., Peters, J., & Sugiyama, M. (2009). Efficient Sample Reuse in EM-Based Policy Search. In W. Buntine, M. Grobelnik, D. Mladenic, & J. Shaw-Taylor (Eds.), Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2009, Bled, Slovenia, September 7-11, 2009 (pp. 469-484). Berlin, Germany: Springer.

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 Creators:
Hachiya, H, Author              
Peters, J1, 2, Author              
Sugiyama, M, Author
Affiliations:
1Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497795              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497794              

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 Abstract: Direct policy search is a promising reinforcement learning framework in particular for controlling in continuous, high-dimensional systems such as anthropomorphic robots. Policy search often requires a large number of samples for obtaining a stable policy update estimator due to its high flexibility. However, this is prohibitive when the sampling cost is expensive. In this paper, we extend a EM-based policy search method so that previously collected samples can be efficiently reused. The usefulness of the proposed method, called Reward-weighted Regression with sample Reuse, is demonstrated through a robot learning experiment.

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 Dates: 2009-09
 Publication Status: Published in print
 Pages: -
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 Table of Contents: -
 Rev. Type: -
 Identifiers: DOI: 10.1007/978-3-642-04180-8_48
BibTex Citekey: 6068
 Degree: -

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Title: 16th European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2009)
Place of Event: Bled, Slovenia
Start-/End Date: 2009-09-07 - 2009-09-11

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Title: Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2009, Bled, Slovenia, September 7-11, 2009
Source Genre: Proceedings
 Creator(s):
Buntine, W, Editor
Grobelnik, M, Editor
Mladenic, D, Editor
Shaw-Taylor, J, Editor
Affiliations:
-
Publ. Info: Berlin, Germany : Springer
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 469 - 484 Identifier: ISBN: 978-3-642-04179-2

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Title: Lecture Notes in Computer Science
Source Genre: Series
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Pages: - Volume / Issue: 5781 Sequence Number: - Start / End Page: - Identifier: -