| Paper Abstract and Keywords |
| Presentation |
2008-03-28 11:15
Action Learning by An Artificial Neural Network Risa Shimada, Kenya Jin'no (KGUniv.) NLP2007-170 |
| Abstract |
(in Japanese) |
(See Japanese page) |
| (in English) |
We would like to understand a learning feature of human. To realize such purpose, we try to learn an action by artificial neural networks. In this article, we consider an operation to load a building block into Tetris as a simple problem which is two dimensional problem. In order to learn an action, we use a supervised learning algorithm and a reinforcement learning algorith. For the supervised learning, namely, backpropergation algorithm, our numerical simulation result indicates that we cannot get a desired learning reslut. However, we confirm that the reinforcement learning algorithm conduces to a desired learning result which the block can be moved toward to the lowest location. Based on the result of reinforcement learning, we modify the backpropagation algorithm. Consequently, we confirm that the backpropagation algorithm endows the neural network with a generalized ability. |
| Keyword |
(in Japanese) |
(See Japanese page) |
| (in English) |
neural network / back propagation / reinforcement learning / Tetris / / / / |
| Reference Info. |
IEICE Tech. Rep., vol. 107, no. 561, NLP2007-170, pp. 19-24, March 2008. |
| Paper # |
NLP2007-170 |
| Date of Issue |
2008-03-21 (NLP) |
| 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 |
NLP2007-170 |
| Conference Information |
| Committee |
NLP |
| Conference Date |
2008-03-27 - 2008-03-28 |
| Place (in Japanese) |
(See Japanese page) |
| Place (in English) |
|
| Topics (in Japanese) |
(See Japanese page) |
| Topics (in English) |
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| Paper Information |
| Registration To |
NLP |
| Conference Code |
2008-03-NLP |
| Language |
Japanese |
| Title (in Japanese) |
(See Japanese page) |
| Sub Title (in Japanese) |
(See Japanese page) |
| Title (in English) |
Action Learning by An Artificial Neural Network |
| Sub Title (in English) |
|
| Keyword(1) |
neural network |
| Keyword(2) |
back propagation |
| Keyword(3) |
reinforcement learning |
| Keyword(4) |
Tetris |
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| 1st Author's Name |
Risa Shimada |
| 1st Author's Affiliation |
Kanto Gakuin University (KGUniv.) |
| 2nd Author's Name |
Kenya Jin'no |
| 2nd Author's Affiliation |
Kanto Gakuin University (KGUniv.) |
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| Speaker |
Author-1 |
| Date Time |
2008-03-28 11:15:00 |
| Presentation Time |
25 minutes |
| Registration for |
NLP |
| Paper # |
NLP2007-170 |
| Volume (vol) |
vol.107 |
| Number (no) |
no.561 |
| Page |
pp.19-24 |
| #Pages |
6 |
| Date of Issue |
2008-03-21 (NLP) |