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| Presentation | 2023-03-03 13:10 Study on the resilient role in coordinated behavior of a triad using deep reinforcement learning and rule-based modeling Jun Ichikawa (Shizuoka Univ.), Kazushi Tsutsui, Keisuke Fujii (Nagoya Univ.)  HCS2022-93 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | Group can often implement a task, which is difficult to do alone, or achieve higher performance than an individual. For such coordination, adjustments based on two types of information processing are crucial; (1) bottom-up of obtaining and using other members' states through haptic and visual senses and (2) top-down based on a group goal, task limitations, and a role. However, coordinated group behavior is not fully investigated from both processing. Meanwhile, our previous study conducted the behavioral experiment; triads repeatedly engaged in a coordinated drawing task where participants changed tensions by reels, shared heterogeneous roles, and moved a pen connected to the three threads to draw an equilateral triangle. The results suggested that a resilient role, which adjusted to help others and improve situations, was related to performance. In such a role, the above-mentioned processing would work; this study investigated the resilient role in the task using deep reinforcement learning and rule-based modeling. The simulation results indicated that the condition, in which an agent in this role acted by bottom-up and top-down processing, achieved higher performance (smaller pen deviation) than the only rule-based and random conditions. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | coordinated group behavior / role sharing / resilience / deep reinforcement learning / rule-based modeling / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 122, no. 413, HCS2022-93, pp. 100-105, March 2023. | |
| Paper # | HCS2022-93 | |
| Date of Issue | 2023-02-23 (HCS) | |
| 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 | HCS2022-93 |
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| Conference Information | |
| Committee | HCS |
| Conference Date | 2023-03-02 - 2023-03-03 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Tokoha University（KusanagiCampus） |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Interaction modeling, etc. |
| Paper Information | |
| Registration To | HCS |
| Conference Code | 2023-03-HCS |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Study on the resilient role in coordinated behavior of a triad using deep reinforcement learning and rule-based modeling |
| Sub Title (in English) | |
| Keyword(1) | coordinated group behavior |
| Keyword(2) | role sharing |
| Keyword(3) | resilience |
| Keyword(4) | deep reinforcement learning |
| Keyword(5) | rule-based modeling |
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| 1st Author's Name | Jun Ichikawa |
| 1st Author's Affiliation | Shizuoka University (Shizuoka Univ.) |
| 2nd Author's Name | Kazushi Tsutsui |
| 2nd Author's Affiliation | Nagoya University (Nagoya Univ.) |
| 3rd Author's Name | Keisuke Fujii |
| 3rd Author's Affiliation | Nagoya University (Nagoya Univ.) |
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| Speaker | Author-1 |
| Date Time | 2023-03-03 13:10:00 |
| Presentation Time | 30 minutes |
| Registration for | HCS |
| Paper # | HCS2022-93 |
| Volume (vol) | vol.122 |
| Number (no) | no.413 |
| Page | pp.100-105 |
| #Pages | 6 |
| Date of Issue | 2023-02-23 (HCS) |
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