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| Paper Abstract and Keywords | ||
| Presentation | 2023-01-29 14:25 Continuous Value Control of Robot with Reservoir Actor-Critic Model Koutaro Minato, Yuichi Katori (Future Univ Hakodate)  NLP2022-103 NC2022-87 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | Deep learning is expected to be utilized to control robots operating in complex environments, but this requires a large amount of data, training time, and power. Robot control using reservoir computing (RC) has been proposed as a method to solve this problem, but the control method when the control signal is a continuous value has yet to be elucidated. In this study, the actor-critic method, one of the reinforcement learning methods, is combined with RC to construct a model of robot control that requires control by continuous values. We report that the reservoir actor-critic model performs well in a car mountain climbing task (MountainCarContinuous-v0), which requires continuous-valued control. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | reservoir computing / reinforcement learning / actor-critic method / continuous action space / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 122, no. 374, NC2022-87, pp. 118-122, Jan. 2023. | |
| Paper # | NC2022-87 | |
| Date of Issue | 2023-01-21 (NLP, NC) | |
| 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) | |
| Download PDF | NLP2022-103 NC2022-87 |
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| Conference Information | |
| Committee | NC NLP |
| Conference Date | 2023-01-28 - 2023-01-29 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Future University Hakodate |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | NC, NLP, etc. |
| Paper Information | |
| Registration To | NC |
| Conference Code | 2023-01-NC-NLP |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Continuous Value Control of Robot with Reservoir Actor-Critic Model |
| Sub Title (in English) | |
| Keyword(1) | reservoir computing |
| Keyword(2) | reinforcement learning |
| Keyword(3) | actor-critic method |
| Keyword(4) | continuous action space |
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| 1st Author's Name | Koutaro Minato |
| 1st Author's Affiliation | Future University Hakodate (Future Univ Hakodate) |
| 2nd Author's Name | Yuichi Katori |
| 2nd Author's Affiliation | Future University Hakodate (Future Univ Hakodate) |
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| Speaker | Author-1 |
| Date Time | 2023-01-29 14:25:00 |
| Presentation Time | 25 minutes |
| Registration for | NC |
| Paper # | NLP2022-103, NC2022-87 |
| Volume (vol) | vol.122 |
| Number (no) | no.373(NLP), no.374(NC) |
| Page | pp.118-122 |
| #Pages | 5 |
| Date of Issue | 2023-01-21 (NLP, NC) |
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