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| Presentation | 2018-01-23 14:25 Community Extraction Using Online Battle Data for Game AIs Capable to Infer Imperfect Information Ryohei Watanabe, Komei Arasawa, Shun Hattori (Muroran Inst. of Tech.)  IN2017-87 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | In these days, playing video games competitively, called “e-sports,” is getting in fashion. But most of video games are imperfect information games, thus it is not always easy for players to select a behavior accurately in a video game. Therefore, our research aims to build a game AI capable to infer imperfect information based on online battle data acquired from an online battle environment for a video game, and to help online battles between players. This paper applies community extraction to online battle data (e.g., usage rate of characters, their status and properties, etc.) for a game AI to infer imperfect information, and analyzes the characteristics of extracted communities. Our game AI tries to learn about the tendency of players’ tactics selection in the current battle environment from the results of the analysis, and utilizes it for her/his own tactics selection. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | Game AI / Imperfect Information / Community Extraction / Open Date / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 117, no. 397, IN2017-87, pp. 91-96, Jan. 2018. | |
| Paper # | IN2017-87 | |
| Date of Issue | 2018-01-15 (IN) | |
| 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 | IN2017-87 |
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| Conference Information | |
| Committee | IN |
| Conference Date | 2018-01-22 - 2018-01-23 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | WINC AICHI |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Contents Distribution, Social Networking Services, Data Analytics and Processing Platform, Big data, etc. |
| Paper Information | |
| Registration To | IN |
| Conference Code | 2018-01-IN |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Community Extraction Using Online Battle Data for Game AIs Capable to Infer Imperfect Information |
| Sub Title (in English) | |
| Keyword(1) | Game AI |
| Keyword(2) | Imperfect Information |
| Keyword(3) | Community Extraction |
| Keyword(4) | Open Date |
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| 1st Author's Name | Ryohei Watanabe |
| 1st Author's Affiliation | Muroran Institute of Technology (Muroran Inst. of Tech.) |
| 2nd Author's Name | Komei Arasawa |
| 2nd Author's Affiliation | Muroran Institute of Technology (Muroran Inst. of Tech.) |
| 3rd Author's Name | Shun Hattori |
| 3rd Author's Affiliation | Muroran Institute of Technology (Muroran Inst. of Tech.) |
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| Speaker | Author-1 |
| Date Time | 2018-01-23 14:25:00 |
| Presentation Time | 25 minutes |
| Registration for | IN |
| Paper # | IN2017-87 |
| Volume (vol) | vol.117 |
| Number (no) | no.397 |
| Page | pp.91-96 |
| #Pages | 6 |
| Date of Issue | 2018-01-15 (IN) |
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