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Paper Abstract and Keywords
Presentation 2026-08-04 14:35
An Attempt at Data-Driven Simulation of Decision-Making Support in Human-AI Collaboration Considering User Personality
Yosuke Fukuchi (TMU), Seiji Yamada (Kanagawa Univ.) CNR2026-2
Abstract (in Japanese) (See Japanese page) 
(in English) This paper explores a framework for designing AI assistance strategies that account for users' individual characteristics in a data-driven manner, using an AI-assisted stock trading simulation as a testbed. The underlying idea is that the strategy for presenting AI recommendations to support user decision making should be determined based on three factors: the performance of the AI, the user's own decision-making ability, and the user's individual characteristics. To examine this framework, we first conducted a user study and confirmed that both reliance on AI recommendations and final task performance are influenced by these three factors. Next, we showed that incorporating individual characteristics into a data-driven user model improves its fidelity in reproducing users' behavior across sequences of decisions. Finally, using the user model with individual characteristics, we simulated how decisions evolve over time and counterfactually evaluated multiple assistance strategies. The results suggest that the proposed framework can contribute to generating hypotheses about assistance strategies that take into account the interplay of AI performance, user ability, and individual characteristics.
Keyword (in Japanese) (See Japanese page) 
(in English) Human-AI collaborative decision-making / Personal characteristics / User model / Digital twin / / / /  
Reference Info. IEICE Tech. Rep., vol. 126, no. 139, CNR2026-2, pp. 7-11, Aug. 2026.
Paper # CNR2026-2 
Date of Issue 2026-07-28 (CNR) 
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 CNR2026-2

Conference Information
Committee CNR  
Conference Date 2026-08-04 - 2026-08-04 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To CNR 
Conference Code 2026-08-CNR 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) An Attempt at Data-Driven Simulation of Decision-Making Support in Human-AI Collaboration Considering User Personality 
Sub Title (in English)  
Keyword(1) Human-AI collaborative decision-making  
Keyword(2) Personal characteristics  
Keyword(3) User model  
Keyword(4) Digital twin  
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1st Author's Name Yosuke Fukuchi  
1st Author's Affiliation Tokyo Metropolitan University (TMU)
2nd Author's Name Seiji Yamada  
2nd Author's Affiliation Kanagawa University (Kanagawa Univ.)
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Speaker Author-1 
Date Time 2026-08-04 14:35:00 
Presentation Time 30 minutes 
Registration for CNR 
Paper # CNR2026-2 
Volume (vol) vol.126 
Number (no) no.139 
Page pp.7-11 
#Pages 5 
Date of Issue 2026-07-28 (CNR) 

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