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Paper Abstract and Keywords
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
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)
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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
Date of Issue 2018-01-15 (IN) 


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