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| Presentation | 2022-01-23 10:55 Reward-oriented Environment Inference on Reinforcement Learning Kazuki Takahashi (Kogakuin Univ.), Tomoki Fukai (OIST), Yutaka Sakai (Tamagawa Univ.), Takashi Takekawa (Kogakuin Univ.)  NC2021-42 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | Experiments on humans using the bandit problem have shown that dimensionality reduction of complex observations to a state suitable for reward prediction can improve the speed of learning optimal behavior. Therefore, we propose reward-oriented environment inference that reduces the complicated observation to the state representation suitable for reward prediction. In addition, we also propose a model-based decision-making method using Thompson sampling. In the results, we discuss the dimensionality reduction of states and learning of strategies by a reward-oriented environment estimation model through simulation. |
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| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | variational inference / reinforcement learning / thompson sampling / dimensionality reduction / environment inference / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 121, no. 338, NC2021-42, pp. 49-54, Jan. 2022. | |
| Paper # | NC2021-42 | |
| Date of Issue | 2022-01-14 (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 | NC2021-42 |
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| Conference Information | |
| Committee | NLP MICT MBE NC |
| Conference Date | 2022-01-21 - 2022-01-23 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Online |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Paper Information | |
| Registration To | NC |
| Conference Code | 2022-01-NLP-MICT-MBE-NC |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Reward-oriented Environment Inference on Reinforcement Learning |
| Sub Title (in English) | |
| Keyword(1) | variational inference |
| Keyword(2) | reinforcement learning |
| Keyword(3) | thompson sampling |
| Keyword(4) | dimensionality reduction |
| Keyword(5) | environment inference |
| Keyword(6) | |
| Keyword(7) | |
| Keyword(8) | |
| 1st Author's Name | Kazuki Takahashi |
| 1st Author's Affiliation | Kogakuin University (Kogakuin Univ.) |
| 2nd Author's Name | Tomoki Fukai |
| 2nd Author's Affiliation | Okinawa Institute of Science and Technology Graduate University (OIST) |
| 3rd Author's Name | Yutaka Sakai |
| 3rd Author's Affiliation | Tamagawa University (Tamagawa Univ.) |
| 4th Author's Name | Takashi Takekawa |
| 4th Author's Affiliation | Kogakuin University (Kogakuin Univ.) |
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| Speaker | Author-1 |
| Date Time | 2022-01-23 10:55:00 |
| Presentation Time | 25 minutes |
| Registration for | NC |
| Paper # | NC2021-42 |
| Volume (vol) | vol.121 |
| Number (no) | no.338 |
| Page | pp.49-54 |
| #Pages | 6 |
| Date of Issue | 2022-01-14 (NC) |
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