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| Presentation | 2007-12-22 15:45 Adaptive Importance Sampling with Automatic Model Selection in Value Function Approximation Hirotaka Hachiya, Takayuki Akiyama, Masashi Sugiyama (Tokyo Inst. of Tech.)  NC2007-84 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | Off-policy reinforcement learning is aimed at efficiently reusing data samples gathered in the past. A common approach is to use importance sampling techniques for compensating for the bias caused by the difference between data-collecting policies and the target policy. However, existing off-policy methods do not often take the variance of value function estimators explicitly into account and therefore their performance tends to be unstable. To cope with this problem, we propose using an adaptive importance sampling technique which allows us to actively control the trade-off between bias and variance. We further provide a method for optimally determining the trade-off parameter based on a statistical machine learning theory. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | Off-policy / Reinforcement learning / Value function approximation / Importance sampling / Importance weighted cross validation / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 107, no. 410, NC2007-84, pp. 75-80, Dec. 2007. | |
| Paper # | NC2007-84 | |
| Date of Issue | 2007-12-15 (NC) | |
| ISSN | Print edition: ISSN 0913-5685 Online edition: ISSN 2432-6380 | |
| Copyright and reproduction |
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034) | |
| Download PDF | NC2007-84 |
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| Conference Information | |
| Committee | MBE NC |
| Conference Date | 2007-12-22 - 2007-12-22 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Paper Information | |
| Registration To | NC |
| Conference Code | 2007-12-MBE-NC |
| Language | English |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Adaptive Importance Sampling with Automatic Model Selection in Value Function Approximation |
| Sub Title (in English) | |
| Keyword(1) | Off-policy |
| Keyword(2) | Reinforcement learning |
| Keyword(3) | Value function approximation |
| Keyword(4) | Importance sampling |
| Keyword(5) | Importance weighted cross validation |
| Keyword(6) | |
| Keyword(7) | |
| Keyword(8) | |
| 1st Author's Name | Hirotaka Hachiya |
| 1st Author's Affiliation | Tokyo Institute of Technology (Tokyo Inst. of Tech.) |
| 2nd Author's Name | Takayuki Akiyama |
| 2nd Author's Affiliation | Tokyo Institute of Technology (Tokyo Inst. of Tech.) |
| 3rd Author's Name | Masashi Sugiyama |
| 3rd Author's Affiliation | Tokyo Institute of Technology (Tokyo Inst. of Tech.) |
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| Speaker | Author-1 |
| Date Time | 2007-12-22 15:45:00 |
| Presentation Time | 25 minutes |
| Registration for | NC |
| Paper # | NC2007-84 |
| Volume (vol) | vol.107 |
| Number (no) | no.410 |
| Page | pp.75-80 |
| #Pages | 6 |
| Date of Issue | 2007-12-15 (NC) |
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