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Paper Abstract and Keywords
Presentation 2022-09-30 10:30
An approximation algorithm for computing integrated information based on Gaussian process regression
Tadaaki Hosaka (TUS) NC2022-40
Abstract (in Japanese) (See Japanese page) 
(in English) The framework of Integrated Information Theory, which aims to mathematically deal with consciousness, consists of multiple computationally-expensive combinatorial optimizations. Therefore, they are not practically feasible for systems with a large number of nodes. The objective of this study is to construct an approximation algorithm for computing the integrated information using the Gaussian process regression and Bayesian optimization. In the proposed method, each optimization problem is approximately solved by estimation based on the Gaussian process regression. The integrated information obtained by the proposed method is highly correlated with the exact solution under certain conditions.
Keyword (in Japanese) (See Japanese page) 
(in English) Integrated information theory / Approximation algorithm / Intrinsic difference / Bayesian optimization / / / /  
Reference Info. IEICE Tech. Rep., vol. 122, no. 195, NC2022-40, pp. 32-37, Sept. 2022.
Paper # NC2022-40 
Date of Issue 2022-09-22 (NC) 
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 NC2022-40

Conference Information
Committee NC MBE  
Conference Date 2022-09-29 - 2022-09-30 
Place (in Japanese) (See Japanese page) 
Place (in English) Tohoku Univ. 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Brain Architecture, NC, ME 
Paper Information
Registration To NC 
Conference Code 2022-09-NC-MBE 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) An approximation algorithm for computing integrated information based on Gaussian process regression 
Sub Title (in English)  
Keyword(1) Integrated information theory  
Keyword(2) Approximation algorithm  
Keyword(3) Intrinsic difference  
Keyword(4) Bayesian optimization  
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1st Author's Name Tadaaki Hosaka  
1st Author's Affiliation Tokyo University of Science (TUS)
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Speaker Author-1 
Date Time 2022-09-30 10:30:00 
Presentation Time 25 minutes 
Registration for NC 
Paper # NC2022-40 
Volume (vol) vol.122 
Number (no) no.195 
Page pp.32-37 
#Pages 6 
Date of Issue 2022-09-22 (NC) 

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