Updated on 2024/04/16

写真a

 
NOTSU akira
 
Organization
Graduate School of Sustainable System Sciences Division of Sustainable System Sciences Professor
College of Sustainable System Sciences Department of Psychology
Title
Professor
Affiliation
Institute of Sustainable System Sciences
Contact information
メールアドレス
Affiliation campus
Nakamozu Campus

Position

  • Graduate School of Sustainable System Sciences Division of Sustainable System Sciences 

    Professor  2022.04 - Now

  • College of Sustainable System Sciences Department of Psychology 

    Professor  2022.04 - Now

Degree

  • 博士(情報学) ( Others )

  • 修士(情報学) ( Others )

Research Areas

  • Informatics / Soft computing

  • Humanities & Social Sciences / Cognitive science

  • Informatics / Kansei informatics  / 感性情報学・ソフトコンピューティング

  • Humanities & Social Sciences / Library and information science, humanistic and social informatics

Research Interests

  • 強化学習

  • 適応アルゴリズム

  • 認知モデル

  • 認知的均衡

  • 社会シミュレータ

  • 感性情報処理

  • マルチエージェント

  • データ解析

  • コミュニケーション支援

  • コミュニケーション

  • ケア支援

  • クラスター分析

Research subject summary

  • 認知モデルに基づいた学習アルゴリズム

  • 進化計算・適応アルゴリズム

  • エージェントシミュレーション

  • 人に優しい人工知能

Professional Memberships

  • Japan Society for Fuzzy Theory and Intelligent Informatics

    2012.01 - Now

  • アートミーツケア学会

    2007.10 - Now

  • ヒューマンインタフェース学会

    2003.08 - Now

  • 計測自動制御学会

    2002.01 - Now

Awards

  • Best Student Paper Award

    M. Iguchi, A. Notsu, K. Yasunaga, S. Ubukata, K. Honda

    2022.11   iFuzzy 2022 Committee   Deep Reinforcement Learning Combined with Approximation of Number of State Experiences

     More details

    Country:Taiwan, Province of China

    In action selection policy during deep reinforcement learning, it is possible to balance exploration and utilization efficiently by considering the selection frequency of state action pairs. However, when the similarity of states is also learned in parallel, it is difficult to accurately count how many times each state has been reached in the past. In this paper, we propose a new method to estimate the value of each state in consideration of the balance between exploration and exploitation by constructing a network which estimates only whether or not the state has been reached in the past but has no reward. The frequency of state reached should simply increase as learning progresses, so we set such a function. The policy takes into account the mean and variance of the beta distribution constructed from reward values and their experience values. The effectiveness of the proposed method is confirmed by numerical experiments.

  • Excellent Paper Award

    2020.09   International Symposium on Community-centric Systems 2020  

  • 最優秀論文賞

    2017.10   ISIS2017 国際会議委員会  

  • 優秀論文賞

    2016.10   FANシンポジウム運営委員会  

     More details

    Country:Japan

  • Best Paper Award

    2016.08   Joint 8th International Conference on Soft Computing and Intelligent Systems and 17th International Symposium on Advanced Intelligent Systems  

  • 優秀論文賞

    2015.09   FANシンポジウム運営委員会  

     More details

    Country:Japan

  • Best Session Paper Award

    2013.11   14th International Symposium on Advanced Intelligent Systems  

  • 日本知能情報ファジィ学会論文賞

    2012.09   日本知能情報ファジィ学会  

  • FANプレゼンテーション賞

    2011.09   FAN2011委員会  

  • 日本知能情報ファジィ学会論文賞

    2011.09   日本知能情報ファジィ学会  

  • Best Paper Award

    2009.09   the 19th Intelligent System Symposium & the 1st International Workshop on Aware Computing  

  • Best Paper Award

    2009.08   10th International Symposium on Advanced Intelligent Systems  

  • Best Paper Award

    2008.06   2008 IEEE International Conference on Fuzzy Systems  

▼display all

Job Career (off-campus)

  • Osaka Prefecture University

    2015 - Now

Papers

  • Addition of Out-of-Population Search in JADE

    MIYAHIRA Yuichi, IGUCHI Makishi, NOTSU Akira, HONDA Katsuhiro

    Journal of Japan Society for Fuzzy Theory and Intelligent Informatics   35 ( 1 )   532 - 537   2023.02( ISSN:13477986

     More details

    <p>JADE is an optimization algorithm that uses probability distributions to adaptively select parameters. However, it does not take into account the search for regions outside the solution population, so it can be improved by adding an efficient out-of-population search such as the Nelder-Mead method. In this study, a simple method with a small number of parameters to add out-of-population search was considered while keeping the search speed as high as possible, and its effectiveness was confirmed through numerical experiments.</p>

    DOI: 10.3156/jsoft.35.1_532

  • FCM-Induced Switching Fuzzy Factorization Machine for Collaborative Filtering

    Daido R.

    IEEE International Conference on Fuzzy Systems   2023( ISSN:10987584 ( ISBN:9798350332285

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  • Switching Non-negative Matrix Factorization with Partial Distance Strategy for Incomplete Data

    Okabe Akira, Honda Katsuhiro, Ubukata Seiki, Notsu Akira

    Proceedings of the Fuzzy System Symposium   39 ( 0 )   79 - 82   2023

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    <p>Non-negative matrix factorization (NMF) is a basic method for analyzing the intrinsic structure of such non-negative matrices as environmental observation data, but cannot work well when datasets include incomplete data subsets drawn from different generative schemes. This paper proposes a novel switching NMF algorithm with partial distance strategy, which simultaneously achieves construction of cluster-wise submodels and handling of missing values.</p>

    DOI: 10.14864/fss.39.0_79

  • Development of AI Line Heating System for Automated Manufacturing of Ship Hulls

    KATO Takuya, HIROSE Sora, MAEDA Shintaro, IKUSHIMA Kazuki, NOTSU Akira, SHIBAHARA Masakazu

    Preprints of the National Meeting of JWS   2023s ( 0 )   142 - 143   2023

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  • A Study on Robust ANFIS Classifier Based on Noise Fuzzy Clustering

    Kitamori Koki, Honda Katsuhiro, Ubukata Seiki, Notsu Akira

    Proceedings of the Japan Joint Automatic Control Conference   66 ( 0 )   633 - 637   2023

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  • Predicting Stock Price Fluctuations Considering the Sunny Effect

    Nakaniwa K.

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)   14376 LNAI   47 - 54   2023( ISSN:03029743 ( ISBN:9783031467806

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  • Handling of Component-Wise Noise in ANFIS Induced by Ellipsoidal Fuzzy Clustering

    Honda K.

    IEEE International Conference on Fuzzy Systems   2023( ISSN:10987584 ( ISBN:9798350332285

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  • A Federated Learning Model of Fuzzy c-Lines for Horizontally Distributed Database

    Honda Katsuhiro, Amejima Ryosuke, Ubukata Seiki, Notsu Akira

    Proceedings of the Fuzzy System Symposium   39 ( 0 )   385 - 387   2023

     More details

    <p>Privacy preserving data clustering is a useful method for extractingintrinsic cluster structures from distributed databases keeping personal privacy. In this research, a novel model of performing Fuzzy c-Lines clustering with horizontally distributed data is proposed, where federated learning is achieved by sharing gradient information estimatedin each client. The proposed model is an extension of the Fuzzy c-Means-type federated learning model proposed by Pedrycz to linear clustering with least square criterion.</p>

    DOI: 10.14864/fss.39.0_385

  • Deep Reinforcement Learning Combined with Approximation of Number of State Experiences Reviewed

    M. Iguchi, A. Notsu, K. Yasunaga, S. Ubukata, K. Honda

    Proc. of 2022 International Conference on Fuzzy Theory and Its Applications   #0012   2022.11

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    Authorship:Corresponding author   Publishing type:Research paper (international conference proceedings)   International / domestic magazine:International journal  

  • Addition of Out-of-population Search Based on the Rate of Solution Updates in JADE Reviewed

    Y. Miyahira, A. Notsu, K. Honda

    Proc. of 2022 International Conference on Fuzzy Theory and Its Applications   #0077   2022.11

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    Authorship:Corresponding author   Publishing type:Research paper (international conference proceedings)   International / domestic magazine:International journal  

  • A Noise Clustering-induced Robust Adaptive Network-based Fuzzy Inference System for Classification

    Honda K.

    Proceedings of the International Joint Conference on Neural Networks   2022-July   2022( ISBN:9781728186719

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  • Handling of Missing Values in Fuzzy c-Lines for Vertically Distributed Database

    Kunisawa Kohei, Honda Katsuhiro, Ubukata Seiki, Notsu Akira

    Proceedings of the Fuzzy System Symposium   38 ( 0 )   571 - 575   2022

     More details

    <p>Privacy preserving data clustering is a useful method for extracting intrinsic cluster structures from distributed databases keeping personal privacy. In this research, a novel model of performing Fuzzy c-Lines clustering is proposed, where a privacy preserving scheme of k-means-type model is adopted with cryptographic calculation ignoring the influences of missing values. The element-wise clustering criterion enables to derive local principal component vectors in each data sources by considering minimization of low-rank approximation of observed elements only.</p>

    DOI: 10.14864/fss.38.0_571

  • Development of Surrogate Model for Fast Prediction of Residual Stress and Its Application

    KATO Takuya, HIROSE Sora, TANGO Yoshihiko, KOMADA Shuji, YAMAUCHI Yuki, NOZU Ryo, IKUSHIMA Kazuki, SHIBAHARA Masakazu

    Preprints of the National Meeting of JWS   2022f ( 0 )   226 - 227   2022

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  • Robust Switching Non-negative Matrix Factorization Based on Noise Fuzzy Clustering

    Furukawa Tomoaki, Honda Katsuhiro, Ubukata Seiki, Notsu Akira

    Proceedings of the Fuzzy System Symposium   38 ( 0 )   685 - 688   2022

     More details

    <p>Non-negative matrix factorization (NMF) is a basic method for analyzing the intrinsic structure of such non-negative matrices as environmental observation data, but cannot work well when datasets include some noisy subsets drawn from different generative schemes. This paper proposes a novel robust switching NMF algorithm, which simultaneously estimates multiple NMF models in conjunction with noise cluster supported by a noise fuzzy clustering concept. The NMF least square measure is modified by introducing noise/non-noise fuzzy memberships of each object, and object fuzzy partition estimation and cluster-wise local NMF modeling are iteratively performed based on the iterative optimization principle utilizing noise cluster.</p>

    DOI: 10.14864/fss.38.0_685

  • A Consideration on k-Means-type Switching Factorization Machine

    Honda Katsuhiro, Daido Rikuto, Ubukata Seiki, Notsu Akira

    Proceedings of the Japan Joint Automatic Control Conference   65 ( 0 )   1494 - 1496   2022

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  • Addition of out-of-population search based on the rate of solution updates in JADE

    Miyahira Yuichi, Notsu Akira, Honda Katsuhiro

    Proceedings of the Fuzzy System Symposium   38 ( 0 )   276 - 280   2022

     More details

    <p>JADE is an optimization algorithm that uses probability distributions to adaptively select parameters. However, it does not take into account the search for regions outside the solution population, so it can be improved by adding an efficient out-of-population search such as the Nelder-Mead method. In this study, a simple method with a small number of parameters to add out-of-population search was considered while keeping the search speed as high as possible, and its effectiveness was confirmed through numerical experiments.</p>

    DOI: 10.14864/fss.38.0_276

  • Handling of Missing Values in FCM Clustering-based ANFIS with Partial Distance Strategy

    Honda K.

    2022 Joint 12th International Conference on Soft Computing and Intelligent Systems and 23rd International Symposium on Advanced Intelligent Systems, SCIS and ISIS 2022   2022( ISBN:9781665499248

  • Fuzzy c-Lines for Vertically Distributed Database with Missing Values

    Kunisawa K.

    2022 Joint 12th International Conference on Soft Computing and Intelligent Systems and 23rd International Symposium on Advanced Intelligent Systems, SCIS and ISIS 2022   2022( ISBN:9781665499248

  • Robust Fuzzy Factorization Machine with Noise Clustering-based Membership Function Estimation Reviewed

    K. Honda, K. Hoshii, S. Ubukata, A. Notsu

    Soft Computing Letters 雑誌   3 ( 100024 )   2021.12

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    Kind of work:Joint Work  

  • Three-mode Fuzzy Co-clustering Based on Probabilistic Concept and Comparison with FCM-type algorithms Reviewed

    K. Honda, I. Hayashi, S. Ubukata, A. Notsu

    Journal of Advanced Computational Intelligence and Intelligent Informatics 雑誌   25 ( 4 )   478 - 488   2021.07

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    Kind of work:Joint Work  

  • ノイズファジィクラスタリング機構に基づくロバスト非負値行列分解と環境観測値分析への応用 Reviewed

    本多 克宏,上野 雅哲,生方 誠希,野津 亮

    日本知能情報ファジィ学会誌 雑誌   33 ( 2 )   593 - 599   2021.05

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    Kind of work:Joint Work  

  • プライバシー保護を考慮した分散データベースの線形ファジィクラスタリング Reviewed

    本多 克宏,國澤 昂平,生方 誠希,野津 亮

    日本知能情報ファジィ学会誌 雑誌   33 ( 2 )   600 - 607   2021.05

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    Kind of work:Joint Work  

  • Objective function-based rough membership C-means clustering Reviewed

    S. Ubukata, A. Notsu, K. Honda

    Information Sciences 雑誌 Elsevier   548   479 - 496   2021.02

  • Online state space generation by a growing self-organizing map and differential learning for reinforcement learning Reviewed

    A. Notsu, K. Yasuda, S. Ubukata, K. Honda

    Applied Soft Computing 雑誌 Elsevier   97 ( 106723 )   1 - 9   2020.12

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    Kind of work:Joint Work  

  • Noise Rejection Approaches for Various Rough Set-Based C-Means Clustering Reviewed

    S. Ubukata, S. Sekiya, A. Notsu, K. Honda

    Journal of Advanced Computational Intelligence and Intelligent Informatics 雑誌 Fuji Technology Press   24 ( 6 )   738 - 749   2020.11

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    Kind of work:Joint Work  

  • Designation of Candidate Solutions in Differential Evolution Based on Bandit Algorithm and its Evaluation Reviewed

    M. Sakakibara, A. Notsu, S. Ubukata, K. Honda

    Journal of Advanced Computational Intelligence and Intelligent Informatics 雑誌   23 ( 4 )   758 - 766   2019.07

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    Kind of work:Joint Work  

  • Visual Co-cluster Assessment with Intuitive Cluster Validation through Cooccurrence-Sensitive Ordering Reviewed

    K. Honda, T. Sako, S. Ubukata, A. Notsu

    Journal of Advanced Computational Intelligence and Intelligent Informatics 雑誌   22 ( 5 )   585 - 592   2018.09

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    Kind of work:Joint Work  

  • Rough Set-Based Clustering Utilizing Probabilistic Memberships Reviewed

    S. Ubukata, H. Kato, A. Notsu, K. Honda

    Journal of Advanced Computational Intelligence and Intelligent Informatics 雑誌   22 ( 6 )   956 - 964   2018.09

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    Kind of work:Joint Work  

  • MMMs-Induced Possibilistic Fuzzy Co-Clustering and its Characteristics Reviewed

    S. Ubukata, K. Koike, A. Notsu, K. Honda

    Journal of Advanced Computational Intelligence and Intelligent Informatics 雑誌   22 ( 5 )   747 - 758   2018.09

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    Kind of work:Joint Work  

  • Characteristics of Rough Set C-Means Clustering Reviewed

    S. Ubukata, K. Umado, A. Notsu, K. Honda

    Journal of Advanced Computational Intelligence and Intelligent Informatics 雑誌   22 ( 4 )   551 - 564   2018.07

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    Kind of work:Joint Work  

  • Spectral Ordering に基づく共クラスタ構造の視覚化とその特徴 Reviewed

    佐古拓也, 本多克宏, 生方誠希, 野津 亮

    システム制御情報学会論文誌 雑誌   31 ( 5 )   177 - 183   2018.05

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    Kind of work:Joint Work  

  • Deterministic Annealing Process for pLSA-induced Fuzzy Co-clustering and Cluster Splitting Characteristics Reviewed

    T. Goshima, K. Honda, S. Ubukata, A. Notsu

    International Journal of Approximate Reasoning 雑誌   95   185 - 193   2018.04

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    Kind of work:Joint Work  

  • FCM-type Fuzzy Coclustering for Three-mode Cooccurrence Data: 3FCCM and 3Fuzzy CoDoK Reviewed

    K. Honda, Y. Suzuki, S. Ubukata, A. Notsu

    Advances in Fuzzy Systems 雑誌   9842127   1 - 8   2017.12

  • Noise Rejection in MMMs-induced Fuzzy Co-clustering Reviewed

    K. Honda, N. Yamamoto, S. Ubukata, A. Notsu

    Journal of Advanced Computational Intelligence and Intelligent Informatics 雑誌   21 ( 7 )   1144 - 1151   2017.11

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    Kind of work:Joint Work  

  • General Formulation of Rough C-Means Clustering Reviewed

    S. Ubukata, A. Notsu, K. Honda

    International Journal of Computer Science and Network Security 雑誌   17 ( 9 )   29 - 38   2017.09

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    Kind of work:Joint Work  

  • プロスペクト理論を応用したベータ分布伝搬型強化学習による効率的探索と活用 Reviewed

    野津 亮, 生方誠希, 本多克宏

    日本知能情報ファジィ学会誌 雑誌   29 ( 1 )   507 - 516   2017.02

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    Kind of work:Joint Work  

  • Two Phase Implementation of MMMs-induced Fuzzy Co-clustering with Partially Exclusive Item Assignment Reviewed

    T. Nakano, K. Honda, S. Ubukata, A. Notsu

    International Journal of Computer Science and Network Security 雑誌   17 ( 1 )   67 - 72   2017.01

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    Kind of work:Joint Work  

  • Visualization of Learning Process in "State and Action" Space Using Self-Organizing Maps Reviewed

    A. Notsu, Y. Hattori, S. Ubukata, K. Honda

    Journal of Advanced Computational Intelligence and Intelligent Informatics 雑誌   20 ( 6 )   983 - 991   2016.11

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    Kind of work:Joint Work  

  • Fuzzy Clustering-based k-anonymization of Eigen-face Features for Crowd Movement Analysis with Privacy Consideration Reviewed

    K. Honda, M. Omori, S. Ubukata, A. Notsu

    International Journal of Innovative Computing, Information and Control 雑誌   12 ( 4 )   1375 - 1384   2016.08

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    Kind of work:Joint Work  

  • A Semi-supervised Framework for MMMs-induced Fuzzy Co-clustering with Virtual Samples Reviewed

    D. Tanaka, K. Honda, S. Ubukata, A. Notsu

    Advances in Fuzzy Systems 雑誌   2016 ( 5206048 )   1 - 8   2016.06

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    Kind of work:Joint Work  

  • ファジィk-memberクラスタリングによる顔画像匿名化を伴うプライバシー保護群集行動分析 Reviewed

    本多克宏, 大森正博, 生方誠希, 野津亮

    システム制御情報学会論文誌 雑誌   29 ( 3 )   130 - 135   2016.03

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    Kind of work:Joint Work  

  • Consideration of Site-wise Confidence in Fuzzy Co-clustering of Vertically Distributed Cooccurrence Data Reviewed

    T. Oda, K. Honda, S. Ubukata, A. Notsu

    International Journal of Computer Science and Network Security 雑誌   16 ( 2 )   15 - 21   2016.02

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    Kind of work:Joint Work  

  • バンディットアルゴリズムに基づいた汎用最適化手法の開発 Reviewed

    野津亮, 河上寛和, 本多克宏, 生方誠希

    日本知能情報ファジィ学会誌 雑誌   28 ( 1 )   522 - 534   2016.02

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    Kind of work:Joint Work  

  • Deterministic Annealing Framework in MMMs-Induced Fuzzy Co-Clustering and Its Applicability Reviewed

    S. Oshio, K. Honda, S. Ubukata, A. Notsu

    International Journal of Computer Science and Network Security 雑誌   16 ( 1 )   43 - 60   2016.01

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    Kind of work:Joint Work  

  • Partially Exclusive Item Partition in MMMs-induced Fuzzy Co-clustering and Its Effects in Collaborative Filtering Reviewed

    K. Honda, T. Nakano, C.-H. Oh, S. Ubukata, A. Notsu

    Journal of Advanced Computational Intelligence and Intelligent Informatics 雑誌   19 ( 6 )   810 - 817   2015.11

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    Kind of work:Joint Work  

  • Fuzzy Co-clustering Induced by Multinomial Mixture Models Reviewed

    K. Honda, S. Oshio, A. Notsu

    Journal of Advanced Computational Intelligence and Intelligent Informatics 雑誌   19 ( 6 )   717 - 726   2015.11

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    Kind of work:Joint Work  

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Books and Other Publications

  • Lecture Notes in Computer Science

    Akira Notsu, Osamu Katai, Hiroshi Kawakami( Role: Joint author)

       2001.04 

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    Responsible for pages:279-290  

Presentations

  • Fuzzy Bag-of-Words Based Evaluation Data Imputation for Collaborative Filtering International conference

    K. Honda, T. Youkawa, S. Ubukata, A. Notsu

    The 5th International Conference on Ambient Intelligence and Ergonomics in Asia  2021.03 

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    Presentation type:Poster presentation  

  • ファジィ共クラスタリングにおけるファジィ・可能性分割の導入 Domestic conference

    本多 克宏,林 昂佑,生方 誠希,野津 亮

    第63回自動制御連合講演会  2020.11 

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    Presentation type:Poster presentation  

  • ノイズクラスタリングの概念に基づくファジィ推論のロバスト化 Domestic conference

    本多 克宏,百武 慧,生方 誠希,野津 亮

    第63回自動制御連合講演会  2020.11 

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    Presentation type:Poster presentation  

  • Randomness Selection in Differential Evolution Using Thompson Sampling International conference

    A. Notsu, J. Tsubamoto, Y. Miyahira, S. Ubukata, K. Honda

    Joint 11th International Conference on Soft Computing and Intelligent Systems and 21st International Symposium on Advanced Intelligent Systems  2020.11 

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    Presentation type:Poster presentation  

  • Basic Consideration of Collaborative Filtering Based on Rough C-Means Clustering International conference

    S. Ubukata, S. Takahashi, A. Notsu, K. Honda

    Joint 11th International Conference on Soft Computing and Intelligent Systems and 21st International Symposium on Advanced Intelligent Systems  2020.11 

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    Presentation type:Poster presentation  

  • Basic Consideration of Rough C-Medoids Clustering with Minkowski Distance International conference

    S. Ubukata, A. Sugimoto, A. Notsu, K. Honda

    Joint 11th International Conference on Soft Computing and Intelligent Systems and 21st International Symposium on Advanced Intelligent Systems  2020.11 

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    Presentation type:Poster presentation  

  • Basic Consideration of Co-Clustering Based on Rough Set Theory International conference

    S. Ubukata, N. Nodake, A. Notsu, K. Honda

    8th International Symposium on Integrated Uncertainty in Knowledge Modelling and Decision Making  2020.11 

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    Presentation type:Poster presentation  

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Charge of on-campus class subject

  • 人間情報システム特論

    2023   Weekly class   Graduate school

  • 未来デザイン計画演習

    2023   Intensive lecture   Undergraduate

  • 人間環境科学演習II(心理演習)

    2023   Weekly class   Undergraduate

  • 認知情報処理

    2023   Weekly class   Undergraduate

  • 環境システム学卒業研究

    2023   Intensive lecture   Undergraduate

  • 環境システム学演習III

    2023   Weekly class   Undergraduate

  • 初年次ゼミナール

    2023   Weekly class   Undergraduate

  • 未来デザインインターンシップ

    2023   Intensive lecture   Undergraduate

  • 心理学実験

    2023   Weekly class   Undergraduate

  • 認知科学2(学習・言語心理学)

    2023   Weekly class   Undergraduate

  • 環境システム学演習IV

    2023   Weekly class   Undergraduate

  • 認知行動科学特別研究1

    2022   Intensive lecture   Graduate school

  • 人間情報システム特論

    2022   Weekly class   Graduate school

  • 現代システム科学特別演習1

    2022   Intensive lecture   Graduate school

  • 認知科学演習I

    2022   Intensive lecture   Undergraduate

  • 環境システム学演習III

    2022   Weekly class   Undergraduate

  • 初年次ゼミナール

    2022   Weekly class   Undergraduate

  • 心理学特別研究1

    2022   Intensive lecture   Graduate school

  • 心理学特別演習1

    2022   Intensive lecture   Graduate school

  • 人間環境科学演習II(心理演習)

    2022   Weekly class   Undergraduate

  • 認知科学II(学習・言語心理学)

    2022   Weekly class   Undergraduate

  • 環境システム学演習I

    2022   Weekly class   Undergraduate

  • 環境システム学特別研究VI

    2022   Intensive lecture   Graduate school

  • 環境システム学特別研究VIII

    2022   Intensive lecture   Graduate school

  • 心理学特別演習2

    2022   Intensive lecture   Graduate school

  • 心理学特別研究2

    2022   Intensive lecture   Graduate school

  • 現代システム科学特別演習2

    2022   Intensive lecture   Graduate school

  • 認知行動科学特別研究2

    2022   Intensive lecture   Graduate school

  • 未来デザインインターンシップ

    2022   Intensive lecture   Undergraduate

  • 環境システム学特別研究VII

    2022   Intensive lecture   Graduate school

  • 環境システム学卒業研究

    2022   Intensive lecture   Undergraduate

  • 環境システム学演習IV

    2022   Weekly class   Undergraduate

  • 認知情報処理

    2022   Weekly class   Undergraduate

  • Special Seminar in Psychology and Social Environment B

    2021    

  • Special Seminar in Psychology and Social Environment A

    2021    

  • Special Research on Environmental System Sciences II

    2021    

  • Special Research on Environmental System Sciences I

    2021    

  • Seminar in Cognitive Science I

    2021    

  • Intelligent System Design

    2021    

  • Cognitive Information Processing II

    2021    

  • Graduation Research in Environmental System Sciences

    2021    

  • Special Topics in Human Information System

    2021    

  • Introduction to Programming

    2021    

  • Seminar in Human Environmental Science II

    2021    

  • Seminar in Environmental System Sciences I

    2021    

  • Cognitive Science II

    2021    

  • Seminar in Environmental System Sciences IV

    2021    

  • Seminar in Environmental System Sciences III

    2021    

  • Cognitive Information Processing

    2021    

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Visiting Lectures ⇒ Link to the list of Visiting Lectures

  • 人間のように考えるロボットって?

    Category:Modern system science (knowledge information system, environmental system, educational welfare, psychology), Engineering (machinery, electronics / physics, electrical / electronics, electrical information, chemical biotechnology, architecture, cities (civil engineering / environment), material chemistry, aerospace, marine systems, applied chemistry, chemistry, materials)

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    Audience:Preschooler, Schoolchildren, Junior high school students, Teachers, Researchers, Company, Civic organization

    Keyword:強化学習,マルチエージェント,社会心理学,認知工学 

    認知的情報圧縮や忘却などを利用し探索空間を小さくする知的エージェントや人工システムデザインを紹介します