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Paper Abstract and Keywords
Presentation 2021-02-27 14:00
A System for Joining Body Part Motions Using Reinforcement Learning
Takumu Matsushita, Asako Soga (Ryukoku Univ)
Abstract (in Japanese) (See Japanese page) 
(in English) In this study, we developed a system for joining body-part motions using reinforcement learning with the aim of supporting the creation of choreography. The system generates short choreographic motions and displays animations of them. The generated motions are learned based on feature values using reinforcement learning. In order to verify that learning with different weights generates motions with different characteristics, an evaluation of impressions was conducted by having subjects compare generated motions. As a result, it was found that the larger the weight given, the greater the immobility.
Keyword (in Japanese) (See Japanese page) 
(in English) Machine Learning / Reinforcement Learning / Animation / Motion Synthesis / Creation Support / / /  
Reference Info. ITE Tech. Rep., vol. 45, no. 6, ME2021-43, pp. 57-58, Feb. 2021.
Paper # ME2021-43 
Date of Issue 2021-02-20 (ME) 
ISSN Print edition: ISSN 1342-6893    Online edition: ISSN 2424-1970
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Conference Information
Committee ME  
Conference Date 2021-02-27 - 2021-02-27 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
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Paper Information
Registration To ME 
Conference Code 2021-02-ME 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A System for Joining Body Part Motions Using Reinforcement Learning 
Sub Title (in English)  
Keyword(1) Machine Learning  
Keyword(2) Reinforcement Learning  
Keyword(3) Animation  
Keyword(4) Motion Synthesis  
Keyword(5) Creation Support  
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1st Author's Name Takumu Matsushita  
1st Author's Affiliation Ryukoku University (Ryukoku Univ)
2nd Author's Name Asako Soga  
2nd Author's Affiliation Ryukoku University (Ryukoku Univ)
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Speaker Author-1 
Date Time 2021-02-27 14:00:00 
Presentation Time 15 minutes 
Registration for ME 
Paper # ME2021-43 
Volume (vol) vol.45 
Number (no) no.6 
Page pp.57-58 
#Pages
Date of Issue 2021-02-20 (ME) 


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