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Paper Abstract and Keywords
Presentation 2024-01-18 11:30
Deep Reinforcement Learning Using LMM's Studying Papers and Intrinsic Rewards
Sota Nagano, Satoshi Yamane (Kanazawa Univ.) MSS2023-64 SS2023-43
Abstract (in Japanese) (See Japanese page) 
(in English) Research combining deep reinforcement learning with a large language model (LLM) produced high scores even for open-world games with complex tasks. However, LLM cannot handle images that represent the appearance of the game, and natural language is required to describe the state of the environment. Therefore, we propose a deep reinforcement learning method (LMMPaIR) based on a large multimodal model (LMM) that can handle both images and language. We use LMMs to extract information for successful game play from pictures and captions in a paper about the environment, and generate intrinsic rewards from this information. We are currently experimenting with LMMPaIR in combination with the reinforcement learning algorithm PPO in the Crafter.
Keyword (in Japanese) (See Japanese page) 
(in English) Machine Learning / Deep Reinforcement Learning / Large Language Model / Large Multimodal Model / / / /  
Reference Info. IEICE Tech. Rep., vol. 123, no. 334, MSS2023-64, pp. 70-75, Jan. 2024.
Paper # MSS2023-64 
Date of Issue 2024-01-10 (MSS, SS) 
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 MSS2023-64 SS2023-43

Conference Information
Committee SS MSS  
Conference Date 2024-01-17 - 2024-01-18 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To MSS 
Conference Code 2024-01-SS-MSS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Deep Reinforcement Learning Using LMM's Studying Papers and Intrinsic Rewards 
Sub Title (in English)  
Keyword(1) Machine Learning  
Keyword(2) Deep Reinforcement Learning  
Keyword(3) Large Language Model  
Keyword(4) Large Multimodal Model  
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1st Author's Name Sota Nagano  
1st Author's Affiliation Kanazawa University (Kanazawa Univ.)
2nd Author's Name Satoshi Yamane  
2nd Author's Affiliation Kanazawa University (Kanazawa Univ.)
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Speaker Author-1 
Date Time 2024-01-18 11:30:00 
Presentation Time 25 minutes 
Registration for MSS 
Paper # MSS2023-64, SS2023-43 
Volume (vol) vol.123 
Number (no) no.334(MSS), no.335(SS) 
Page pp.70-75 
#Pages 6 
Date of Issue 2024-01-10 (MSS, SS) 

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