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| Paper Abstract and Keywords | ||
| Presentation | 2017-06-29 13:30 A Complex-Valued Reinforcement Learning Method Using Complex-Valued Neural Networks Masaki Mochida, Hidehiro Nakano, Arata Miyauchi (Tokyo City Univ.)  CCS2017-1 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | This paper proposes the method to approximate the action-value function in complex-valued reinforcement learning by using complex-valued neural networks. Complex-valued reinforcement learning extends action–values to complex numbers and adding action-values to some context information enables the learning algorithm to adapt perceptual aliasing with less memory usage. In order to apply larger environment with the large number of sates, this paper introduces the function approximation for the action-value function by using complex-valued neural networks. We perform simulation experiments on the Mountain Car environment which has continuous states. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | reinforcement learning / perceptual aliasing / complex-valued reinforcement learning / complex-valued neural networks / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 117, no. 112, CCS2017-1, pp. 1-5, June 2017. | |
| Paper # | CCS2017-1 | |
| Date of Issue | 2017-06-22 (CCS) | |
| 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 | CCS2017-1 |
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| Conference Information | |
| Committee | CCS |
| Conference Date | 2017-06-29 - 2017-06-30 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Ibaraki Univ. |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Interaction and Communication, etc. |
| Paper Information | |
| Registration To | CCS |
| Conference Code | 2017-06-CCS |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | A Complex-Valued Reinforcement Learning Method Using Complex-Valued Neural Networks |
| Sub Title (in English) | |
| Keyword(1) | reinforcement learning |
| Keyword(2) | perceptual aliasing |
| Keyword(3) | complex-valued reinforcement learning |
| Keyword(4) | complex-valued neural networks |
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| 1st Author's Name | Masaki Mochida |
| 1st Author's Affiliation | Tokyo City University (Tokyo City Univ.) |
| 2nd Author's Name | Hidehiro Nakano |
| 2nd Author's Affiliation | Tokyo City University (Tokyo City Univ.) |
| 3rd Author's Name | Arata Miyauchi |
| 3rd Author's Affiliation | Tokyo City University (Tokyo City Univ.) |
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| Speaker | Author-1 |
| Date Time | 2017-06-29 13:30:00 |
| Presentation Time | 25 minutes |
| Registration for | CCS |
| Paper # | CCS2017-1 |
| Volume (vol) | vol.117 |
| Number (no) | no.112 |
| Page | pp.1-5 |
| #Pages | 5 |
| Date of Issue | 2017-06-22 (CCS) |
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