Paper Abstract and Keywords |
Presentation |
2020-06-29 15:25
A Study on Model-based Deep Reinforcement Learning Using Autonomous Search for Subgoal Motoki Maruyama, Satoshi Endo, Koji Yamada (Univ. of the Ryukyus) NC2020-6 IBISML2020-6 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
Model-based deep reinforcement learning (DRL) is more sample-efficient than model-free DRL. But it requires a deep generative model to learn an accurate dynamics. Therefore, it is difficult to deep lookahead depth due to a realistic cost. In this work, We propose to compare the subgoals with the shallow lookahead depth and give rewards according to the proximity by decomposing the tasks and setting subgoals. This method achieve a certain result in the maze. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Deep reinforcement learning / Subgoals / Model-based / DQN / GANs / / / |
Reference Info. |
IEICE Tech. Rep., vol. 120, no. 79, NC2020-6, pp. 33-38, June 2020. |
Paper # |
NC2020-6 |
Date of Issue |
2020-06-22 (NC, IBISML) |
ISSN |
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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NC2020-6 IBISML2020-6 |
Conference Information |
Committee |
NC IBISML IPSJ-BIO IPSJ-MPS |
Conference Date |
2020-06-29 - 2020-06-29 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Online |
Topics (in Japanese) |
(See Japanese page) |
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Paper Information |
Registration To |
NC |
Conference Code |
2020-06-NC-IBISML-BIO-MPS |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
A Study on Model-based Deep Reinforcement Learning Using Autonomous Search for Subgoal |
Sub Title (in English) |
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Keyword(1) |
Deep reinforcement learning |
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Subgoals |
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Model-based |
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DQN |
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GANs |
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1st Author's Name |
Motoki Maruyama |
1st Author's Affiliation |
University of the Ryukyus (Univ. of the Ryukyus) |
2nd Author's Name |
Satoshi Endo |
2nd Author's Affiliation |
University of the Ryukyus (Univ. of the Ryukyus) |
3rd Author's Name |
Koji Yamada |
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University of the Ryukyus (Univ. of the Ryukyus) |
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Speaker |
Author-1 |
Date Time |
2020-06-29 15:25:00 |
Presentation Time |
25 minutes |
Registration for |
NC |
Paper # |
NC2020-6, IBISML2020-6 |
Volume (vol) |
vol.120 |
Number (no) |
no.79(NC), no.80(IBISML) |
Page |
pp.33-38 |
#Pages |
6 |
Date of Issue |
2020-06-22 (NC, IBISML) |
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