| Paper Abstract and Keywords |
| Presentation |
2023-03-01 09:30
Modification and Comparison of Learning Sudoku with Convolutional Networks Koichiro Ishii, Hiroshi Tamura (Chuo Univ.) CAS2022-96 CS2022-73 |
| Abstract |
(in Japanese) |
(See Japanese page) |
| (in English) |
Sudoku is a logic puzzle in which the number between 1 and 9 is to fill in the boxes of the 9x9 grid by using the numbers already filled in as clues. Recently, graph convolutional networks (GCNs) have been developing as a deep learning method for graph structures. In this paper, we attempt to solve a Sudoku puzzle applied to a graph structure by using GCN. Although there have already been studies using convolutional neural networks (CNN), it is difficult to understand the computational process. On the other hand, GCN model can refer to the clues with which you solve a Sudoku puzzle, so we thought that the learning and computation processes can be made closer to the human solving process. We also believe that GCN has the flexibility to adapt to Sudoku and other puzzles having different rules by applying them to graph structures. In this paper, we compared the results with those of conventional neural networks and verified the difference in accuracy of the network model by changing the feature values and internal calculation parameter. |
| Keyword |
(in Japanese) |
(See Japanese page) |
| (in English) |
Sudoku / Graph Theory / Machine Learning / Graph Convolutional Network / / / / |
| Reference Info. |
IEICE Tech. Rep., vol. 122, no. 396, CAS2022-96, pp. 1-5, March 2023. |
| Paper # |
CAS2022-96 |
| Date of Issue |
2023-02-22 (CAS, CS) |
| 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 |
CAS2022-96 CS2022-73 |
| Conference Information |
| Committee |
CAS CS |
| Conference Date |
2023-03-01 - 2023-03-02 |
| Place (in Japanese) |
(See Japanese page) |
| Place (in English) |
Kitakyushu International Conference Center |
| Topics (in Japanese) |
(See Japanese page) |
| Topics (in English) |
Network processor, Signal processing and circuits for communications, Wireless LAN / PAN, etc. |
| Paper Information |
| Registration To |
CAS |
| Conference Code |
2023-03-CAS-CS |
| Language |
Japanese |
| Title (in Japanese) |
(See Japanese page) |
| Sub Title (in Japanese) |
(See Japanese page) |
| Title (in English) |
Modification and Comparison of Learning Sudoku with Convolutional Networks |
| Sub Title (in English) |
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| Keyword(1) |
Sudoku |
| Keyword(2) |
Graph Theory |
| Keyword(3) |
Machine Learning |
| Keyword(4) |
Graph Convolutional Network |
| Keyword(5) |
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| Keyword(6) |
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| Keyword(7) |
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| Keyword(8) |
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| 1st Author's Name |
Koichiro Ishii |
| 1st Author's Affiliation |
Chuo University (Chuo Univ.) |
| 2nd Author's Name |
Hiroshi Tamura |
| 2nd Author's Affiliation |
Chuo University (Chuo Univ.) |
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| Speaker |
Author-1 |
| Date Time |
2023-03-01 09:30:00 |
| Presentation Time |
25 minutes |
| Registration for |
CAS |
| Paper # |
CAS2022-96, CS2022-73 |
| Volume (vol) |
vol.122 |
| Number (no) |
no.396(CAS), no.397(CS) |
| Page |
pp.1-5 |
| #Pages |
5 |
| Date of Issue |
2023-02-22 (CAS, CS) |