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| Presentation | 2018-11-23 10:50 A Human-Like Agent Based on a Hybrid of Reinforcement and Imitation Learning Xinyu Lian, Rousslan Fernand Julien Dossa (Kobe Univ.), Hirokazu Nomoto (EQUOS RESEARCH), Takashi Matsubara, Kuniaki Uehara (Kobe Univ.)  CCS2018-41 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | Reinforcement learning (RL) makes it possible to build an efficient agent that handles tasks in complex and uncertain environments by maximizing future reward. However, for applications in some areas like game AI and autonomous driving, efficiency only cannot satisfy the practical use, and a human-like agent is preferable. On the other hand, in imitation learning (IL) tasks, which trains the agent to mimic actions of expert behavior provided as training data and thereby learns relatively complex tasks while achieving human-like behavior. Unfortunately, the performance of such an agent is generally limited by the expert behavior. Thus, with the aim of training an agent which achieves high performance while retaining a human-like behavior, we propose a method for mixing RL and IL, applicable to both discrete and continuous problems. We used state-of-the-art RL and IL algorithms and trained their respective models independently, before mixing them into the proposed hybrid model. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | Human-Like / Hybrid Model / Reinforcement Learning / Imitation Learning / Game AI / Autonomous Driving / / | |
| Reference Info. | IEICE Tech. Rep., vol. 118, no. 316, CCS2018-41, pp. 45-50, Nov. 2018. | |
| Paper # | CCS2018-41 | |
| Date of Issue | 2018-11-15 (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 | CCS2018-41 |
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| Conference Information | |
| Committee | CCS |
| Conference Date | 2018-11-22 - 2018-11-23 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Kobe Univ. |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Interaction and Communication, etc. |
| Paper Information | |
| Registration To | CCS |
| Conference Code | 2018-11-CCS |
| Language | English |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | A Human-Like Agent Based on a Hybrid of Reinforcement and Imitation Learning |
| Sub Title (in English) | |
| Keyword(1) | Human-Like |
| Keyword(2) | Hybrid Model |
| Keyword(3) | Reinforcement Learning |
| Keyword(4) | Imitation Learning |
| Keyword(5) | Game AI |
| Keyword(6) | Autonomous Driving |
| Keyword(7) | |
| Keyword(8) | |
| 1st Author's Name | Xinyu Lian |
| 1st Author's Affiliation | Kobe University (Kobe Univ.) |
| 2nd Author's Name | Rousslan Fernand Julien Dossa |
| 2nd Author's Affiliation | Kobe University (Kobe Univ.) |
| 3rd Author's Name | Hirokazu Nomoto |
| 3rd Author's Affiliation | EQUOS RESEARCH Co., Ltd. (EQUOS RESEARCH) |
| 4th Author's Name | Takashi Matsubara |
| 4th Author's Affiliation | Kobe University (Kobe Univ.) |
| 5th Author's Name | Kuniaki Uehara |
| 5th Author's Affiliation | Kobe University (Kobe Univ.) |
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| Speaker | Author-1 |
| Date Time | 2018-11-23 10:50:00 |
| Presentation Time | 25 minutes |
| Registration for | CCS |
| Paper # | CCS2018-41 |
| Volume (vol) | vol.118 |
| Number (no) | no.316 |
| Page | pp.45-50 |
| #Pages | 6 |
| Date of Issue | 2018-11-15 (CCS) |
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