Paper Abstract and Keywords |
Presentation |
2012-11-07 15:30
Stochastic policy gradient method for a stochastic policy using a Gaussian process regression Yutaka Nakamura, Hiroshi Ishiguro (Osaka Univ.) IBISML2012-52 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
Reinforcement learning (RL) methods using Gaussian process regression (GP) for approximating the value function have been studied [1]. Thanks to the use of Bayesian reasoning with GPs, the variance of the output can be calculated, but there is no direct benefit by using the variance of the value estimate. In this research, we propose a policy gradient method for a GP based stochastic policy, where the output variance is utilized as the confidence in the action selection. We apply our method to a control task of the swinging up a pendulum, and simulation results show a good controller can be obtained by our method. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Reinforcement learning / Gaussian process regression / policy gradient method / adaptive control / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 112, no. 279, IBISML2012-52, pp. 129-133, Nov. 2012. |
Paper # |
IBISML2012-52 |
Date of Issue |
2012-10-31 (IBISML) |
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) |
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IBISML2012-52 |
Conference Information |
Committee |
IBISML |
Conference Date |
2012-11-07 - 2012-11-09 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Bunkyo School Building, Tokyo Campus, Tsukuba Univ. |
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
the 15th Information-Based Induction Sciences Workshop |
Paper Information |
Registration To |
IBISML |
Conference Code |
2012-11-IBISML |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Stochastic policy gradient method for a stochastic policy using a Gaussian process regression |
Sub Title (in English) |
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Keyword(1) |
Reinforcement learning |
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Gaussian process regression |
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policy gradient method |
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adaptive control |
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1st Author's Name |
Yutaka Nakamura |
1st Author's Affiliation |
Osaka University (Osaka Univ.) |
2nd Author's Name |
Hiroshi Ishiguro |
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Osaka University (Osaka Univ.) |
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Speaker |
Author-1 |
Date Time |
2012-11-07 15:30:00 |
Presentation Time |
150 minutes |
Registration for |
IBISML |
Paper # |
IBISML2012-52 |
Volume (vol) |
vol.112 |
Number (no) |
no.279 |
Page |
pp.129-133 |
#Pages |
5 |
Date of Issue |
2012-10-31 (IBISML) |
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