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| Paper Abstract and Keywords | ||
| Presentation | 2022-09-15 14:55 [Invited Talk] Artificial Intelligence Approaches for Curling Masahito Yamamoto (Hokkaido Univ.)  CQ2022-32 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | Curling is a sport in which players compete for points by delivering stones on the ice, and is one of the official sports of the Winter Olympics. As can be seen from the fact that curling is also called "chess on ice," it is a sport in which strategies are extremely important. While the opposing team is playing, one's own team is not allowed to play, and the players play to create a position where the opponent does not want to play. However, in the case of curling, even if a certain strategy is adopted, there is uncertainty in the outcome depending on the players' skills, the ice conditions, and their judgment of the situation. In this talk, the attempt to apply the artificial intelligence approach that has been successfully applied to competitive games such as Shogi and Go to the sport of curling will be presented. The expected score distribution at the end of "END" for any position is learned using a deep learning method based on the results of a large number of simulations. The learned expected score distribution for a given position can be used to derive the best play, or to analyze which team has the advantage. An actual analysis of a curling match at the 2022 Beijing Olympics will be also introduced. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | artificial intelligence / deep learning / curling / game tree search / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 122, no. 184, CQ2022-32, pp. 49-49, Sept. 2022. | |
| Paper # | CQ2022-32 | |
| Date of Issue | 2022-09-08 (CQ) | |
| 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 | CQ2022-32 |
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| Conference Information | |
| Committee | IA CQ MIKA |
| Conference Date | 2022-09-15 - 2022-09-16 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Hokkaido Citizens Actives Center |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Wireless Communications Quality, 6G, IoT, Cross layer Technologies, Internet Operation and Management, etc. |
| Paper Information | |
| Registration To | CQ |
| Conference Code | 2022-09-IA-CQ-MIKA |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Artificial Intelligence Approaches for Curling |
| Sub Title (in English) | |
| Keyword(1) | artificial intelligence |
| Keyword(2) | deep learning |
| Keyword(3) | curling |
| Keyword(4) | game tree search |
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| 1st Author's Name | Masahito Yamamoto |
| 1st Author's Affiliation | Hokkaido University (Hokkaido Univ.) |
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| Speaker | Author-1 |
| Date Time | 2022-09-15 14:55:00 |
| Presentation Time | 30 minutes |
| Registration for | CQ |
| Paper # | CQ2022-32 |
| Volume (vol) | vol.122 |
| Number (no) | no.184 |
| Page | p.49 |
| #Pages | 1 |
| Date of Issue | 2022-09-08 (CQ) |
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