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Paper Abstract and Keywords
Presentation 2010-11-04 15:00
[Poster Presentation] Learning Evaluation Functions for Shogi Using SVM-based Bipartite Ranking Learning
Daiki Suehiro, Kohei Hatano, Hideo Bannai, Eiji Takimoto, Masayuki Takeda (Kyushu Univ.) IBISML2010-74
Abstract (in Japanese) (See Japanese page) 
(in English) Recently, automatic optimization of parameters by applying machine learning methods has become a mainstream approach for developing good evaluation functions in shogi. However, the features used in the evaluation functions are prepared by the developer, depending heavily on his/her knowledge and intuition. To date, many complex features, such as relationships between multiple pieces, have been designed. In this paper, we propose an approach using polynomial kernels and Support Vector Machines (SVM), where only very simple features will be prepared explicitly. Polynomial kernels allow us to consider high dimensional, n-ary relations of monomial features. We further regard the problem of evaluation function learning as a bipartite ranking problem of the positions after legal moves, and propose a method which uses SVMs (ranking SVM). We show the effectiveness of our algorithm through computational experiments.
Keyword (in Japanese) (See Japanese page) 
(in English) evaluation function / SVM / polynomial kernel / ranking learning / / / /  
Reference Info. IEICE Tech. Rep., vol. 110, no. 265, IBISML2010-74, pp. 113-118, Nov. 2010.
Paper # IBISML2010-74 
Date of Issue 2010-10-28 (IBISML) 
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 IBISML2010-74

Conference Information
Committee IBISML  
Conference Date 2010-11-04 - 2010-11-06 
Place (in Japanese) (See Japanese page) 
Place (in English) IIS, Univ. of Tokyo 
Topics (in Japanese) (See Japanese page) 
Topics (in English) IBIS 2010 (Workshop on Information-based Induction Sciences) 
Paper Information
Registration To IBISML 
Conference Code 2010-11-IBISML 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Learning Evaluation Functions for Shogi Using SVM-based Bipartite Ranking Learning 
Sub Title (in English)  
Keyword(1) evaluation function  
Keyword(2) SVM  
Keyword(3) polynomial kernel  
Keyword(4) ranking learning  
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1st Author's Name Daiki Suehiro  
1st Author's Affiliation Kyushu University (Kyushu Univ.)
2nd Author's Name Kohei Hatano  
2nd Author's Affiliation Kyushu University (Kyushu Univ.)
3rd Author's Name Hideo Bannai  
3rd Author's Affiliation Kyushu University (Kyushu Univ.)
4th Author's Name Eiji Takimoto  
4th Author's Affiliation Kyushu University (Kyushu Univ.)
5th Author's Name Masayuki Takeda  
5th Author's Affiliation Kyushu University (Kyushu Univ.)
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Speaker Author-1 
Date Time 2010-11-04 15:00:00 
Presentation Time 180 minutes 
Registration for IBISML 
Paper # IBISML2010-74 
Volume (vol) vol.110 
Number (no) no.265 
Page pp.113-118 
#Pages 6 
Date of Issue 2010-10-28 (IBISML) 

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