Researcher Profile and Settings

Master

Affiliation (Master)

• Center for Human Nature Artificial Intelligence and Neuroscience

Affiliation (Master)

• Center for Human Nature Artificial Intelligence and Neuroscience

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Profile and Settings

Profile and Settings

• Name (Japanese)

  Iizuka

• Name (Kana)

  Hiroyuki

• Name

  201401015924395996

Alternate Names

http://kaken.nii.ac.jp/d/r/30396832.ja.html

Achievement

Research Interests

• くすぐり   運動主体感   エージェンシー   感覚統合   意図推定   ヒューマンインターフェイス   バーチャルリアリティ   行動分節化   脳・神経   

Research Areas

• Informatics / Human interfaces and interactions
• Informatics / Intelligent robotics
• Life sciences / Basic brain sciences
• Humanities & social sciences / Cognitive sciences
• Informatics / Database science

Research Experience

• 2023/04 - Today Hokkaido University Center for Human Nature, Artificial Intelligence and Neuroscience Associate Professor
• 2013/10 - 2023/03 Hokkaido University Graduate school of Information Science and Technology Associate Professor
• 2008/10 - 2013/10 Osaka University
• 2008/05 - 2008/09 大阪大学大学院 情報科学研究科 特任助教
• 2005/04 - 2008/03 日本学術振興会 特別研究員（PD)

Education

• 2001/04 - 2004/03  東京大学大学院
• 1999/04 - 2001/03  北海道大学大学院
• 1995/04 - 1999/03  Hokkaido University  School of Engineering  Department of Information Engineering

Awards

• 2019/12 IEEE ALIFE 2019 Best Paper Award
   Analysis of Time Series Generated By Long Short-Term Memory Trained with Adversarial Imitation Learning 

  受賞者: Seiya Yamazaki;Hiroyuki Iizuka;Masahito Yamamoto
• 2018/12 The 22nd Asia Pacific Symposium on Intelligent and Evolutionary Systems Best Paper Award
   Combined Method of YOLO and IOU Tracker for Tracking and Identifying Chimpanzee 

  受賞者: Yuichiro Ikeda;Hiroyuki Iizuka;Masahito Yamamoto
• 2016/09 日本バーチャルリアリティ学会 論文賞
   往復電流刺激が及ぼす前庭電気刺激の身体動揺増大効果のモデル化 

  受賞者: 青山一真;飯塚博幸;櫻井悟;古川正紘;前田太郎;安藤英由樹
• 2014/09 日本バーチャルリアリティ学会 論文賞
   腹腔鏡下手術トレーニングにおける視野共有手法による学習効果とその実証 

  受賞者: 近藤大祐;飯塚博幸;安藤英由樹;小濱和貴;坂井義治;前田太郎

Published Papers

• A Deep Learning Approach to Understanding the Integration of Tools into Body Schema

  Haruna Kasashima, Wataru Noguchi, Yasumasa Tamura, Masahito Yamamoto, Hiroyuki Iizuka

  ALIFE 2024: Proceedings of the 2024 Artificial Life Conference 2024/07 [Refereed]
  
• Analyzing the Sensibility of Visual Language Models Using an Evolving Image Generation System: Focusing on Color Impressions and Sound Symbolism

  Ryoma Shinto, Hiroyuki Iizuka

  ALIFE 2024: Proceedings of the 2024 Artificial Life Conference 2024/07 [Refereed]
  
• 動物園のゾウを対象にした単一監視カメラ映像によるトラッキング手法の検討と実践

  西岡拳, 野口渉, 飯塚博幸, 山本雅人

  情報処理学会論文誌デジタルプラクティス（TDP） 5 (3) 60 - 69 2024/07 [Refereed]
  
• Development of Hierarchical Spatial Cognition through Visuo-Motor Experience by Shared-Module RNN

  野口渉, 飯塚博幸

  第３８回人工知能学会全国大会予稿集 4S1-OS-30a-02 2024/05 [Not refereed][Not invited]
  
• Multi-stream Single Network: Efficient Compressed Video Action Recognition with a Single Multi-input Multi-output Network

  Hayto Terao, Wataru Noguchi, Hiroyuki Iizuka, Masahito Yamamoto

  IEEE ACCESS 12 20983 - 20997 2024/02/08 [Refereed]
  
• Acquiring Viewpoint Transformation to Reuse Self Body Image for Other on Self-Organized Internal Spatial Coordinate System

  Wataru Noguchi, Hiroyuki Iizuka, Masahito Yamamoto

  2023 IEEE International Conference on Development and Learning (ICDL) 2023/11/09
• Detecting Eating Behavior of Elephants in a Zoo Using Temporal Action Localization

  Ken Nishioka, Wataru Noguchi, Hiroyuki Izuka, Masahito Yamamoto

  Sensors and Materials 35 (11(4)) 3927 - 3945 2023/10 [Refereed][Not invited]
  
• Hybrid Life : Integrating biological, artificial, and cognitive systems

  Manuel Baltieri, Hiroyuki Iizuka, Olaf Witkowski, Lana Sinapayen, Keisuke Suzuki

  WIREs Cognitive Science 14 (6) e1662  1939-5078 2023/07/05 [Refereed]
   

  Abstract Artificial life is a research field studying what processes and properties define life, based on a multidisciplinary approach spanning the physical, natural, and computational sciences. Artificial life aims to foster a comprehensive study of life beyond “life as we know it” and toward “life as it could be,” with theoretical, synthetic, and empirical models of the fundamental properties of living systems. While still a relatively young field, artificial life has flourished as an environment for researchers with different backgrounds, welcoming ideas, and contributions from a wide range of subjects. Hybrid Life brings our attention to some of the most recent developments within the artificial life community, rooted in more traditional artificial life studies but looking at new challenges emerging from interactions with other fields. Hybrid Life aims to cover studies that can lead to an understanding, from first principles, of what systems are and how biological and artificial systems can interact and integrate to form new kinds of hybrid (living) systems, individuals, and societies. To do so, it focuses on three complementary perspectives: theories of systems and agents, hybrid augmentation, and hybrid interaction. Theories of systems and agents are used to define systems, how they differ (e.g., biological or artificial, autonomous, or nonautonomous), and how multiple systems relate in order to form new hybrid systems. Hybrid augmentation focuses on implementations of systems so tightly connected that they act as a single, integrated one. Hybrid interaction is centered around interactions within a heterogeneous group of distinct living and nonliving systems. After discussing some of the major sources of inspiration for these themes, we will focus on an overview of the works that appeared in Hybrid Life special sessions, hosted by the annual Artificial Life Conference between 2018 and 2022. This article is categorized under:Neuroscience > Cognition Philosophy > Artificial Intelligence Computer Science and Robotics > Robotics
• Multimodal Plastic Body and Peripersonal Space Representation Developed Through Learning of Visuo-Tactile-Proprioceptive Sensations

  Wataru Noguchi, Hiroyuki Iizuka, Masahito Yamamoto

  ALIFE 2023: Ghost in the Machine: Proceedings of the 2023 Artificial Life Conference 2023/07
• Proprioceptive Drift Can Be Caused by Simple Sensory Prediction

  Harada, K, Noguchi, W, Iizuka, H, Yamamoto, M

  ALIFE 2023: Ghost in the Machine: Proceedings of the 2023 Artificial Life Conference 2023/07
• Multiple Timescales RNNを用いた敵対的模倣学習による時系列の複雑化と構造化

  佐々木 太樹, 野口 渉, 飯塚 博幸, 山本 雅人

  情報処理学会第85回全国大会講演論文集 1 349 - 350 2023/03 [Not refereed]
  
• 対戦相手の手札推定とカードの適応的優先順位にもとづく UNO の戦術決定

  佐藤 辰哉, 野口 渉, 飯塚 博幸, 山本 雅人

  第22回複雑系マイクロシンポジウム講演論文集 42 - 45 2023/03 [Not refereed]
  
• 共有モジュールを用いた予測ネットワークによる対面する他者の視点獲得

  岩崎 智也, 野口 渉, 飯塚 博幸, 山本 雅人

  38 - 41 2023/03 [Not refereed]
  
• 共有モジュールを用いた自己他者重ね合わせによる姿勢模倣

  髙橋 光, 野口 渉, 飯塚 博幸, 山本 雅人

  第22回複雑系マイクロシンポジウム講演論文集 29 - 33 2023/03 [Not refereed]
  
• 多感覚予測モデルを用いたゴム手錯覚シミュレーションにおける固有感覚ドリフト

  原田 航平, 野口 渉, 飯塚 博幸, 山本 雅人

  第22回複雑系マイクロシンポジウム講演論文集 1 - 4 2023/03 [Not refereed]
  
• Learning shared embedding representation of motion and text using contrastive learning

  Junpei Horie, Wataru Noguchi, Hiroyuki Iizuka, Masahito Yamamoto

  Artificial Life and Robotics 28 (1) 148 - 157 1433-5298 2023/02 [Refereed]
  
• Prediction of Protein Function from Tertiary Structure of the Active Site in Heme Proteins by Convolutional Neural Network

  Hiroko X. Kondo, Hiroyuki Iizuka, Gen Masumoto, Yuichi Kabaya, Yusuke Kanematsu, Yu Takano

  Biomolecules 13 (1) 137 - 137 2023/01/09 [Refereed]
   

  Structure–function relationships in proteins have been one of the crucial scientific topics in recent research. Heme proteins have diverse and pivotal biological functions. Therefore, clarifying their structure–function correlation is significant to understand their functional mechanism and is informative for various fields of science. In this study, we constructed convolutional neural network models for predicting protein functions from the tertiary structures of heme-binding sites (active sites) of heme proteins to examine the structure–function correlation. As a result, we succeeded in the classification of oxygen-binding protein (OB), oxidoreductase (OR), proteins with both functions (OB–OR), and electron transport protein (ET) with high accuracy. Although the misclassification rate for OR and ET was high, the rates between OB and ET and between OB and OR were almost zero, indicating that the prediction model works well between protein groups with quite different functions. However, predicting the function of proteins modified with amino acid mutation(s) remains a challenge. Our findings indicate a structure–function correlation in the active site of heme proteins. This study is expected to be applied to the prediction of more detailed protein functions such as catalytic reactions.
• Generation of structured spatial patterns through adversarial imitation learning

  Hiroyuki Iizuka, Wataru Noguchi, Taiki Sasaki, Masahito Yamamoto

  The Evolution of Language Proceedings of the Joint Conference on Language Evolution 2022 317 - 324 2022/09 [Refereed]
  
• Compressed video ensemble based pseudo-labeling for semi-supervised action recognition

  Hayato Terao, Wataru Noguchi, Hiroyuki Iizuka, Masahito Yamamoto

  Machine Learning with Applications 9 (100336) 100336 - 100336 2666-8270 2022/09 [Refereed][Not invited]
  
• Elucidation of the Correlation between Heme Distortion and Tertiary Structure of the Heme-Binding Pocket Using a Convolutional Neural Network

  Hiroko X. Kondo, Hiroyuki Iizuka, Gen Masumoto, Yuichi Kabaya, Yusuke Kanematsu, Yu Takano

  Biomolecules 12 (9) 1172 - 1172 2022/08/24 [Refereed]
   

  Heme proteins serve diverse and pivotal biological functions. Therefore, clarifying the mechanisms of these diverse functions of heme is a crucial scientific topic. Distortion of heme porphyrin is one of the key factors regulating the chemical properties of heme. Here, we constructed convolutional neural network models for predicting heme distortion from the tertiary structure of the heme-binding pocket to examine their correlation. For saddling, ruffling, doming, and waving distortions, the experimental structure and predicted values were closely correlated. Furthermore, we assessed the correlation between the cavity shape and molecular structure of heme and demonstrated that hemes in protein pockets with similar structures exhibit near-identical structures, indicating the regulation of heme distortion through the protein environment. These findings indicate that the tertiary structure of the heme-binding pocket is one of the factors regulating the distortion of heme porphyrin, thereby controlling the chemical properties of heme relevant to the protein function; this implies a structure–function correlation in heme proteins.
• Gradient Climbing Neural Cellular Automata

  Shuto Kuriyama, Wataru Noguchi, Hiroyuki Iizuka, Masahito Yamamoto

  Proceedings of the Artificial Life Conference 2022 407 - 409 2022/07 [Refereed][Not invited]
  
• Generation of Complex Patterns using Coupled Generative Adversarial Networks

  Hiroyuki Iizuka, Taiki Sasaki, Wataru Noguchi, Masahito Yamamoto

  Proceedings of the Artificial Life Conference 2022 298 - 300 2022/07 [Refereed][Not invited]
  
• Bottom-up formation of number representation and top-down understanding of symbolic manipulation

  Shimada Yasuhiro, Noguchi Wataru, Iizuka Hiroyuki, Yamamoto Masahito

  Proceedings of the Artificial Life Conference 2022 147 - 154 2022/07 [Refereed][Not invited]
  
• 視覚と運動の予測学習を通して空間認知を獲得する深層学習モデル

  野口 渉, 飯塚 博幸, 山本 雅人

  システム／制御／情報 66 (4) 139 - 144 2022/04 [Not refereed][Invited]
  
• 畳み込みニューラルネットワークを用いた色の恒常性の学習によるドレスの色の錯視の再現

  市川貴大, 野口渉, 飯塚博幸, 山本雅人

  情報処理学会第84回全国大会 2 861 - 862 2022/03 [Not refereed]
  
• Superposition mechanism as a neural basis for understanding others

  Wataru Noguchi, Hiroyuki Iizuka, Masahito Yamamoto, Shigeru Taguchi

  Scientific Reports 12 (2859) 2022/02 [Refereed]
  
• Multi-modal shared module that enables the bottom-up formation of map representation and top-down map reading

  Wataru Noguchi, Hiroyuki Iizuka, Masahito Yamamoto

  Advanced Robotics 36 (1-2) 85 - 99 0169-1864 2022/01/02 [Refereed]
  
• The shared-module neural network for self/other differentiation and symbol grounding

  Hiroyuki Iizuka

  Proceedings of the twenty-seventh international symposium on Artificial life and Robotics 1124 (1125) 2022/01 [Refereed]
  
• Increasing complexity of symbol sequences in adversarial imitation learning experiment

  Kazufumi Nomura, Wataru Noguchi, Hiroyuki Iizuka, Masahito Yamamoto

  Proceedings of the twenty-seventh international symposium on Artificial life and Robotics 231 - 236 2022/01 [Refereed]
  
• Understanding intention of others through visual predictive learning based on superposition mechanism

  Katsuki Auchi, Wataru Noguchi, Hiroyuki Iizuka, Masahito Yamamoto

  Proceedings of the twenty-seventh international symposium on Artificial life and Robotics 1812 - 1817 2022/01 [Refereed]
  
• 教師ありBarlow Twinsによる少データ手話単語認識のための事前学習

  荒木関 渉, 野口 渉, 飯塚 博幸, 山本 雅人

  第22回公益社団法人計測自動制御学会システムインテグレーション部門講演会 629 - 634 2021/12 [Not refereed]
  
• I3Dを用いたツシマヤマネコの発情兆候検出

  韓靖威, 足立樹, 小泉那於, 野口渉, 飯塚博幸, 山本雅人

  ロボティクス・メカトロニクス講演会2021 （ROBOMECH2021）講演論文集 2021/05 [Not refereed]
  
• カメラ画像を用いた深層学習による水族館の水透明度判定

  高一, 佐藤聡, 西村究, 野口渉, 飯塚博幸, 山本雅人

  ロボティクス・メカトロニクス講演会2021 （ROBOMECH2021）講演論文集 2021/05 [Not refereed]
  
• Electrical Generation of Intranasal Irritating Chemosensation

  Kazuma Aoyama, Nobuhisa Miyamoto, Satoru Sakurai, Hiroyuki Iizuka, Makoto Mizukami, Masahiro Furukawa, Taro Maeda, Hideyuki Ando

  IEEE Access 9 106714 - 106724 2021 [Refereed]
  
• Complexity Growth by Cooperative Interaction in Adversarial Learning

  Taiki Sasaki, Wataru Noguchi, Hiroyuki Iizuka, Masahito Yamamoto

  Proceedings of the twenty-sixth international symposium on Artificial life and Robotics 78 - 83 2021/01 [Refereed][Not invited]
  
• Multi-agent formation by learning communication signals using DIAL in a distributed multi-agent environment

  Hironobu Horiuchi, Wataru Noguchi, Iizuka Hiroyuki, Masahito Yamamoto

  Proceedings of the twenty-sixth international symposium on Artificial life and Robotics 308 - 312 2021/01 [Refereed][Not invited]
  
• 周辺地域の予測レーダ雨量を用いた深層学習による水路の水位予測

  石川拓実, 阿曽克司, 羽黒厚志, 野口渉, 飯塚博幸, 山本雅人

  第21回計測自動制御学会システムインテグレーション部門講演会 2080 - 2083 2020/12 [Not refereed][Not invited]
  
• カメラ映像を用いたYOLOとI3Dによる飼育動物の行動分類

  加藤圭吾, 野口渉, 飯塚博幸, 山本雅人

  "第21回計測自動制御学会システムインテグレーション部門講演会 " 2084 - 2087 2020/12 [Not refereed][Not invited]
  
• Semi-supervised Learning Combining 2DCNNs and Video Compression for Action Recognition

  Hayato Terao, Wataru Noguchi, Hiroyuki Iizuka, Masahito Yamamoto

  2020 International Conference on Vision, Image and Signal Processing(ICVISP 2020) 14 - 6 2020/12 [Refereed][Not invited]
  
• DIALを用いた通信シグナルの学習によるマルチエージェントフォーメーション

  堀内宏信, 野口渉, 飯塚博幸, 山本雅人

  19回情報科学技術フォーラム(FIT2020)講演論文集, 第2分冊 265 - 266 2020/09 [Not refereed][Not invited]
  
• 複数の代表点を用いたSDMMに基づく半教師あり行動認識手法

  寺尾 颯人, 野口 渉, 飯塚 博幸, 山本 雅人

  19回情報科学技術フォーラム(FIT2020)講演論文集, 第3分冊 165 - 166 2020/09 [Not refereed][Not invited]
  
• 深層学習モデルによる自己と他者の共有身体イメージの獲得

  野口 渉, 飯塚 博幸, 山本 雅人

  19回情報科学技術フォーラム(FIT2020)講演論文集, 第2分冊 299 - 300 2020/09 [Not refereed][Not invited]
  
• Artificial Life Next Generation Perspectives: Echoes from the 2018 Conference in Tokyo Editorial Introduction to the ALIFE 2018 Special Issue

  Olaf Witkowski, Takashi Ikegami, Nathaniel Virgo, Mizuki Oka, Hiroyuki Iizuka

  ARTIFICIAL LIFE 26 (1) 1 - 4 1064-5462 2020/04
• Learning of Evaluation Function in Digital Curling Considering the Probability of Scores at Each End

  Kotaro Ataka, Wataru Noguchi, Iizuka Hiroyuki, Masahito Yamamoto

  AAAI20 Workshop, Artificial Intelligence in Team Sports 1 - 6 2020/02 [Refereed][Not invited]
  
• MixMatch based semi-supervised learning for video action recognition using 3D convolutional neural networks

  Hayato Terao, Wataru Noguchi, Hiroyuki Iizuka, Masahito Yamamoto

  Proceedings of the twenty-fifth international symposium on Artificial life and Robotics 305 - 310 2020/01 [Refereed][Not invited]
  
• Efffect of Reactivity Artificial Medaka on Real Medaka

  Katsuki Auchi, Wataru Noguchi, Hiroyuki Iizuka, Masahito Yamamoto

  Proceedings of the twenty-fifth international symposium on Artificial life and Robotics 86 - 89 2020/01 [Refereed][Not invited]
  
• Reinforcement Learning Method with Internal World Model Training

  Kenji Hirata, Hiroyuki Iizuka, Masahito Yamamoto

  Proceedings of the 2020 IEEE/SICE International Symposium on System Integration 201 - 204 2020/01 [Refereed][Not invited]
  
• Analysis of Time Series Trained by Adversarial Imitation Learning in Discrete State Neural Network Model

  Seiya Yamazaki, Hiroyuki Iizuka, Masahito Yamamoto

  Proceedings of the 2020 IEEE/SICE International Symposium on System Integration 182 - 187 2020/01 [Refereed][Not invited]
  
• Complexity of bird song caused by adversarial imitation learning

  Seiya Yamazaki, Hiroyuki Iizuka, Masahito Yamamoto

  Artificial Life and Robotics 25 (1) 124 - 132 2020/01 [Refereed][Not invited]
  
• Analysis of Time Series Generated By Long Short-Term Memory Trained with Adversarial Imitation Learning

  Seiya Yamazaki, Hiroyuki Iizuka, Masahito Yamamoto

  Proceedings of the 2019 IEEE Symposium Series on Computational Intelligence (IEEE SSCI 2019) 224 - 228 2019/12 [Refereed][Not invited]
  
• 分割した集団の学習による役割分担の獲得

  荒木関 渉, 野口 渉, 飯塚 博幸, 山本 雅人

  情報処理北海道シンポジウム2019 2019/10 [Not refereed][Not invited]
  
• Hybrid Synthetic Approach to Animal Interaction

  Hiroyuki Iizuka, Yosuke Nakamoto, Masahito Yamamoto

  Proceedings of the Artificial Life Conference 2019 50 - 51 2019/07 [Refereed][Not invited]
  
• Spatial Representation of Self and Other by Superposition Neural Network Model

  Wataru Noguchi, Hiroyuki Iizuka, Shigeru Taguchi, Masahito Yamamoto

  Proceedings of the Artificial Life Conference 2019 531 - 532 2019/07 [Refereed][Not invited]
  
• 3次元畳み込みニューラルネットワークを用いた店舗における顧客行動の分類

  貝塚 裕, 飯塚 博幸, 山本 雅人

  ロボティクス・メカトロニクス講演会2019 （ROBOMECH2019） 1A1-M05  2019/06 [Not refereed][Not invited]
  
• UAVの空撮画像を利用した産業廃棄物最終処分場の容量推定

  賀川祐太郎, 飯塚博幸, 山本雅人

  第５１回計測自動制御学会北海道支部学術講演会論文集 27 - 30 2019/03 [Not refereed][Not invited]
  
• Developing Evaluation Function by Deep Reinforcement Learning in the Non-Deterministic Game

  安宅耕太郎, 飯塚博幸, 山本雅人

  第18回複雑系マイクロシンポジウム（CSMS2019） 62 - 65 2019/03 [Not refereed][Not invited]
  
• Feature Vector Extraction for Semi-supervised Action Recognition by LSTM Autoencoder

  寺尾颯人, 飯塚博幸, 山本雅人

  第18回複雑系マイクロシンポジウム（CSMS2019） 25 - 30 2019/03 [Not refereed][Not invited]
  
• Differentiation of communication signals using Deep Q-Network

  堀内宏信, 飯塚博幸, 山本雅人

  第18回複雑系マイクロシンポジウム（CSMS2019） 76 - 80 2019/03 [Not refereed][Not invited]
  
• Group Decision Making through Behavioral Interaction in Robot Swarm

  Naohiro Shibuya, Hiroyuki Iizuka, Masahito Yamamoto

  2019 IEEE/SICE International Symposium on System Integration (SII2019) 764 - 769 2019/01 [Refereed][Not invited]
  
• Establishing Mutual Interaction between Artificial and Real Medaka

  Yosuke Nakamoto, Hiroyuki Iizuka, Masahito Yamamoto

  Proceedings of the Twenty-Fourth International Symposium on Artificial Life and Robotics (AROB2019) 633 - 637 2019/01 [Refereed][Not invited]
  
• Adversarial Imitation Learning of Bird Song Modeled with Recurrent Neural Network

  Seiya Yamazaki, Hiroyuki Iizuka, Masahito Yamamoto

  Proceedings of the Twenty-Fourth International Symposium on Artificial Life and Robotics (AROB2019) 162 - 167 2019/01 [Refereed][Not invited]
  
• Modeling place and head-direction cells self-organized in different environments using recurrent neural networks

  Wataru Noguchi, Hiroyuki Iizuka, Masahito Yamamoto

  Proceedings of the Twenty-Fourth International Symposium on Artificial Life and Robotics (AROB2019) 67 - 72 2019/01 [Refereed][Not invited]
  
• Mutual learning between human and machine to develop a human-machine interface to operate multi-DOF robots

  Kei Takada, Hiroyuki Iizuka, Subhransu Maji, Masahito Yamamoto

  Proceedings of the Twenty-Fourth International Symposium on Artificial Life and Robotics (AROB2019) 397 - 403 2019/01 [Refereed][Not invited]
  
• Reinforcement Learning to Create Value and Policy Functions using Minimax Tree Search in Hex

  Kei Takada, Hiroyuki Iizuka, Masahito Yamamoto

  IEEE transactions on Games 12 (1) 63 - 73 2019/01 [Refereed][Not invited]
  
• Navigation behavior based on self-organized spatial representation in hierarchical recurrent neural network

  Wataru Noguchi, Hiroyuki Iizuka, Masahito Yamamoto

  Advanced Robotics 33 (11) 539 - 549 2019/01 [Refereed][Not invited]
  
• Self-tuning neuro-PID controller for indoor entertainment balloon robot

  Hiroya Nagata, Soichiro Yokoyama, Tomohisa Yamashita, Hiroyuki Iizuka, Masahito Yamamoto, Keiji Suzuki, Hidenori Kawamura

  Journal of Robotics and Mechatronics 30 (3) 390 - 396 0915-3942 2018/06 

  Proportional-integral-derivative (PID) controllers are a classical control algorithm that are still widely used owing to their simplicity and accuracy. However, tuning the three parameters is difficult. No methods have been known to determine the exact ideal combination of the P, I, and D gains. Moreover, controlling a system that contains dynamics changes over time using fixed parameters is difficult. A self-tuning neuro-PID controller is applied to a balloon robot for indoor entertainment to enhance its accuracy in following a target trajectory. Our experiment shows the effectiveness of the neuro-PID controller over conventional hand-tuned PID controller.
• Self-Tuning Neuro-PID Controller for Indoor Entertainment Balloon Robot

  Hiroya Nagata, Soichiro Yokoyama, Tomohisa Yamashita, Hiroyuki Iizuka, Masahito Yamamoto, Keiji Suzuki, Hidenori Kawamura

  JOURNAL OF ROBOTICS AND MECHATRONICS 30 (3) 390 - 396 0915-3942 2018/06 

  Proportional-integral-derivative (PID) controllers are a classical control algorithm that are still widely used owing to their simplicity and accuracy. However, tuning the three parameters is difficult. No methods have been known to determine the exact ideal combination of the P, I, and D gains. Moreover, controlling a system that contains dynamics changes over time using fixed parameters is difficult. A self-tuning neuro-PID controller is applied to a balloon robot for indoor entertainment to enhance its accuracy in following a target trajectory. Our experiment shows the effectiveness of the neuro-PID controller over conventional hand-tuned PID controller.
• Reinforcement Learning for Creating Evaluation Function Using Convolutional Neural Network in Hex

  Kei Takada, Hiroyuki Iizuka, Masahito Yamamoto

  Proceedings - 2017 Conference on Technologies and Applications of Artificial Intelligence, TAAI 2017 196 - 201 2018/05/09 [Refereed][Not invited]
   

  An evaluation function in the board game decides the next move for computer AIs, and a high accurate evaluation function leads to a strong computer AI. Recently, the evaluation function using convolutional neural network(CNN) by supervised learning shows high evaluation accuracy. Supervised learning cannot exceed the teachers, but there must be a possibility to create a more accurate evaluation function by using reinforcement learning. In this paper, we proposed an evaluation function using CNN and reinforcement learning with games of self-play in Hex. The proposed evaluation function is tested with the previous evaluation function and world-champion program MoHex2.0. The results show that evaluation accuracy of the proposed evaluation function is higher than the previous evaluation functions, and proposed computer Hex algorithm EZO-CNN obtained a win rate of 60.0% against MoHex2.0 even though the search time of EZO-CNN is shorter than MoHex2.0.
• Beyond AI: A New Epistemology for Artificial Life and Complex Systems, an Introduction to the 2018 ALIFE conference

  Takashi Ikegami, Nathaniel Virgo, Olaf Witkowski, Mizuki Oka, Reiji Suzuki, Hiroyuki Iizuka

  2018 CONFERENCE ON ARTIFICIAL LIFE (ALIFE 2018) 1 - 4 2018
• Self-Tuning Neuro-PID Controller for Indoor Entertainment Balloon Robot.

  Hiroya Nagata, Soichiro Yokoyama, Tomohisa Yamashita, Hiroyuki Iizuka, Masahito Yamamoto, Keiji Suzuki, Hidenori Kawamura

  J. Robotics Mechatronics 30 (3) 390 - 396 2018
• Computer Hex Algorithm Using a Move Evaluation Method Based on a Convolutional Neural Network

  Kei Takada, Hiroyuki Iizuka, Masahito Yamamoto

  Communications in Computer and Information Science 818 19 - 33 1865-0929 2018 [Refereed][Not invited]
   

  In recent years, a move evaluation model using a convolutional neural network (CNN) has been proposed for Go, and it has been shown that CNN can learn professional human moves. Hex is a two-player connection game, which is included in the Computer Olympiad. It is important to consider cell adjacency on the board for a better Hex strategy. To evaluate cell adjacency from various perspectives properly, we propose a CNN model that evaluates all candidate moves by taking as input all sets consisting of 3 mutually adjacent cells. The proposed CNN model is tested against an existing CNN model called “NeuroHex,” and the comparison results show that our CNN model is superior to NeuroHex on a 13×13 board even though our CNN model is trained on an 11×11 board. We also use the proposed model as an ordering function and test it against the world-champion Hex program “MoHex 2.0” on an 11×11 board. The results show that the proposed model can be used as a better ordering function than the ordering function created by minimax tree optimization, and we obtained a win rate of 49.0% against MoHex 2.0 (30 s/move).
• Combined Method of YOLO and IOU Tracker for Tracking and Identifying Chimpanzee

  Yuichiro Ikeda, Hiroyuki Iizuka, Masahito Yamamoto

  The 22nd Asia Pacific Symposium on Intelligent and Evolutionary Systems (IES 2018) 110 - 115 2018 [Refereed][Not invited]
  
• 手話動作分類におけるRCNNモデルの性能評価と内部状態解析

  松田 啓佑, 飯塚 博幸, 山本雅人

  2018年度 人工知能学会全国大会 2631 - 2634 2018 [Not refereed][Not invited]
  
• 畳み込みニューラルネットワークによるチンパンジーの個体識別

  池田 宥一郎, 飯塚 博幸, 山本雅人

  2018年度 人工知能学会全国大会（第32回） 93 - 95 2018 [Not refereed][Not invited]
  
• Emergence of Chaotic Time Series by Adversarial Imitation Learning

  Seiya Yamazaki, Hiroyuki Iizuka, Masahito Yamamoto

  Proceedings of the 2018 Conference on Artificial Life 659 - 664 2018 [Refereed][Not invited]
   

  Bird song is one of the phenomena that increase in complexity through evolution. A complex song is known to be advantageous for survivability and birds are known to learn how to sing a song from each other. From these facts, we have a hypothesis that adversarial imitation learning plays a major role in the evolution process of a complex song. There is a previous study that demonstrates the complexation of a bird song time series by modeling the process of adversarial imitation learning using a logistic map. However, the real bird songs have much variety and time dependencies, like grammar. Therefore, in this study, adversarial imitation learning is modeled using an artificial neural network that can approximate any function. The network learns adversarial imitation using the gradient descent method. By making such changes, the results of our study show that the generated bird songs evolve through the process of adversarial imitation learning to chaos, as seen in the previous models.
• Learning of Individual Sensorimotor Mapping to Form Swarm Behavior from Real Fish Data

  Hiroyuki Iizuka, Yosuke Namamoto, Masahito Yamamoto

  Proceedings of the 2018 Conference on Artificial Life 179 - 185 2018 [Refereed][Not invited]
   

  Swarms of birds and fish produce well-organized behaviors even though each individual only interacts with their neighbors. Previous studies attempted to derive individual interaction rules using heuristic assumptions from data on captured animals. We propose a machine learning method to obtain the sensorimotor mapping mechanism of individuals directly from captured data. Data on swarm behaviors in fish was captured, and individual positions are determined. The sensory inputs and motor outputs are estimated and used as training data. A simple feedforward neural network is trained to learn the sensorimotor mapping of individuals. The trained network is implemented in the simulated environment and resulting swarm behaviors are investigated. As a result, our trained neural network could reproduce the swarm behavior better than the Boids model. The reproduced swarm behaviors are evaluated in terms of three different measures, and the difference from the Boids model is discussed.
• Effect of behavioral complexity on development of spatial recognition

  Wataru Noguchi, Hiroyuki Iizuka, Masahito Yamamoto

  Proceedings of the 2018 Conference on Artificial Life 147 - 154 2018 [Refereed][Not invited]
   

  Animals develop spatial recognition through visuomotor integrated experiences. In nature, animals change their behavior during development and develop spatial recognition. The developmental process of spatial recognition has been previously studied. However, it is unclear how behavior during development affects the development of spatial recognition. To investigate the effect of movement pattern (behavior) on spatial recognition, we simulated the development of spatial recognition using controlled behaviors. Hierarchical recurrent neural networks (HRNNs) with multiple time scales were trained to predict visuomotor sequences of a simulated mobile agent. The spatial recognition developed with HRNNs was compared for various values of randomness of the agent's movement. The experimental results show that spatial recognition was not developed for movements with a randomness that was too small or too large but for movements with intermediate randomness.
• Deep Reinforcement Learning Method Enabling Stable Learning in Multi-Agent Environment

  Kenji Hirata, Hiroyuki Iizuka, Masahito Yamamoto

  Proceedings of the 22nd Asia Pacific Symposium on Intelligent and Evolutionary Systems (IES 2018) 163 - 168 2018 [Refereed][Not invited]
  
• Differentiation of communication signals to establish cooperation using Deep Q-Network

  Hironobu Horiuchi, Hiroyuki Iizuka, Masahito Yamamoto

  Proceedings of the 22nd Asia Pacific Symposium on Intelligent and Evolutionary Systems (IES 2018) 156 - 162 2018 [Refereed][Not invited]
  
• Development of entertainment balloon robot system for an indoor event venue

  Hiroya Nagata, Stefan Walke, Soichiro Yokoyama, Tomohisa Yamashita, Hiroyuki Iizuka, Masahito Yamamoto, Keiji Suzuki, Hidenori Kawamura

  Artificial Life and Robotics 23 (2) 192 - 199 2017/12 [Refereed][Not invited]
  
• Evolution of communication through differentiation of communicative and goal-directed behaviors

  Naohiro Shibuya, Hiroyuki Iizuka, Masahito Yamamoto

  Artificial Life and Robotics 23 (2) 225 - 240 2017/12 [Refereed][Not invited]
  
• A Sensorimotor Signature of the Transition to Conscious Social Perception: Co-regulation of Active and Passive Touch

  Hiroki Kojima, Tom Froese, Mizuki Oka, Hiroyuki Iizuka, Takashi Ikegami

  FRONTIERS IN PSYCHOLOGY 8 (1778) 1664-1078 2017/10 [Refereed][Not invited]
   

  It is not yet well understood how we become conscious of the presence of other people as being other subjects in their own right. Developmental and phenomenological approaches are converging on a relational hypothesis: my perception of a "you" is primarily constituted by another subject's attention being directed toward "me." This is particularly the case when my body is being physically explored in an intentional manner. We set out to characterize the sensorimotor signature of the transition to being aware of the other by re-analyzing time series of embodied interactions between pairs of adults (recorded during a "perceptual crossing" experiment). Measures of turn-taking and movement synchrony were used to quantify social coordination, and transfer entropy was used to quantify direction of influence. We found that the transition leading to one's conscious perception of the other's presence was indeed characterized by a significant increase in one's passive reception of the other's tactile stimulations. Unexpectedly, one's clear experience of such passive touch was consistently followed by a switch to active touching of the other, while the other correspondingly became more passive, which suggests that this intersubjective experience was reciprocally co-regulated by both participants.
• Unconscious improvement in foreign language learning using mismatch negativity neurofeedback: A preliminary study

  Ming Chang, Hiroyuki Iizuka, Hideki Kashioka, Yasushi Naruse, Masahiro Furukawa, Hideyuki Ando, Taro Maeda

  PLOS ONE 12 (6) e0178694  1932-6203 2017/06 [Refereed][Not invited]
   

  When people learn foreign languages, they find it difficult to perceive speech sounds that are nonexistent in their native language, and extensive training is consequently necessary. Our previous studies have shown that by using neurofeedback based on the mismatch negativity event-related brain potential, participants could unconsciously achieve learning in the auditory discrimination of pure tones that could not be consciously discriminated without the neurofeedback. Here, we examined whether mismatch negativity neurofeedback is effective for helping someone to perceive new speech sounds in foreign language learning. We developed a task for training native Japanese speakers to discriminate between 'l' and 'r' sounds in English, as they usually cannot discriminate between these two sounds. Without participants attending to auditory stimuli or being aware of the nature of the experiment, neurofeedback training helped them to achieve significant improvement in unconscious auditory discrimination and recognition of the target words 'light' and 'right'. There was also improvement in the recognition of other words containing 'l' and 'r' (e.g., 'blight' and 'bright'), even though these words had not been presented during training. This method could be used to facilitate foreign language learning and can be extended to other fields of auditory and clinical research and even other senses.
• Cognitive map self-organization from subjective visuomotor experiences in a hierarchical recurrent neural network

  Wataru Noguchi, Hiroyuki Iizuka, Masahito Yamamoto

  ADAPTIVE BEHAVIOR 25 (3) 129 - 146 1059-7123 2017/06 [Refereed][Not invited]
   

  Animals develop and use cognitive maps, which are internal models of the external environment, to understand the spatial characteristics of their natural environment. Previous studies have shown that a hierarchical structure of recurrent neural networks contributes to the extraction of high-level concepts in sequential sensorimotor experiences. However, the previous studies did not focus on the spatial aspects of these experiences and did not acquire cognitive maps. We modified previous models and trained the proposed model with the visuomotor experiences of an agent in a simulated two-dimensional environment. The proposed model was trained to predict future visual and motion inputs even when only one modality was provided (crossmodal prediction). The proposed model correctly predicted visual images, even when the agent experienced unknown paths. Comparisons of the crossmodal predictions of the models under different conditions revealed that the crossmodal predictions related to motion resulted in self-organization of the cognitive map. Further experiments of mental simulation abilities showed that two-way crossmodal predictions (from vision and motion only) were required for consistent generation of vision and motion. These results indicated that predictive learning involving integrated vision and motion was necessary for self-organization of spatial recognition with a cognitive map.
• Attraction basin sphere estimation approach for niching CMA-ES

  Zhuoran Xu, Hiroyuki Iizuka, Masahito Yamamoto

  SOFT COMPUTING 21 (5) 1327 - 1345 1432-7643 2017/03 [Refereed][Not invited]
   

  Many real-world problems are multimodal, which means algorithms should have the ability to find all or most of the multiple solutions as opposed to a single best solution. Niching is the technique that can help evolutionary algorithms to find multiple solutions. Attraction basin sphere estimation (ABSE) is a newly proposed niching method which has the power of inferring the shape of fitness landscapes by spending some extra evaluations. However, when we apply ABSE to genetic algorithms, those extra evaluations lead to an efficiency problem. However, we notice that the combination of ABSE and covariance matrix adaptation evolution strategy will not cause the efficiency problem and have a good performance. This paper implements this idea and performs experiments on a benchmark set provided by CEC 2013 niching methods competition. The algorithm is compared with the best 5 algorithms in the competition. The results show that the proposed algorithm obtains a good result. The features of the proposed algorithm are also discussed in detail.
• DCGANにおける潜在空間上の局在配置を用いた画像融合

  西村 亮, 飯塚 博幸, 山本 雅人

  精密工学会学術講演会講演論文集 公益社団法人 精密工学会 2017 27 - 28 2017 

  DCGANは画像生成モデルの学習手法として注目を集めており，画像の生成には潜在空間上のベクトルを用いる．潜在空間上には学習した画像の特徴が連続的に分布しており，潜在空間上の２点の中間点では2つの画像の特徴を併せもつような画像となる．本研究では既知の画像を潜在空間へ局在配置させる学習を行い，潜在空間と生成画像を関係づけることで異なる性質の画像の融合を試みる．
• Morphological Evolution of Soft Robots by Age-Fitness Pareto Optimization

  Ogawa Jun, Iizuka Hiroyuki, Yamamoto Masahito

  Proceedings of JSPE Semestrial Meeting 公益社団法人 精密工学会 2017 15 - 16 2017 

  Morphological evolution in evolutionary robotics is an important approach for discovering new robot systems and developmental histories of many creatures. Conventional evolutionary robotics used a rigid-bodied robot by human design in computer simulation to verify the effective robotic control systems. However, it is hard to apply the findings of the conventional evolutionary robotics approaches into the development of a real robot like a creature from the evolved robot because there is major difference between the dynamics of the virtual robot and the real robot. In this work, we propose a new method for evolving more complex and controllable soft-bodied robots without some developmental biases in order to get some innovative robotic findings by using the evolved virtual robot. This work found that the evolved soft-bodied robots have more versatility than most of conventional rigid-bodied robots and they got a lot of unintentional morphologies and behavior control systems like real creatures.
• Mobile Robot Localization from First Person View Images based on Recurrent Convolutional Neural Network

  SUGINAKA Izuho, IIZUKA Hiroyuki, YAMAMOTO Masahito

  The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec) 一般社団法人 日本機械学会 2017 2P2 - F02 2017 

  Many robots are pervading environments of human daily life. It is crucial for those robots to estimate the current self-positions. This is called robot localization. In this paper, we propose a method using a recurrent convolutional neural network (RCNN), which is known as one of deep learning, to achieve robot localization. RCNN is a neural network model that has a convolutional architecture known as CNN with recurrent nodes. We train RCNN to estimate the current position of a robot from the view images of the first person perspectives. Our experimental results show that the estimation error decrease when the successive view images are given and it can estimate the current position accurately.

• Reproduction of Swarm Behavior by Learning Individual Rules Using Neural Network

  Yosuke Nakamoto, Hiroyuki Iizuka, Masahito Yamamoto

  2017 IEEE/SICE INTERNATIONAL SYMPOSIUM ON SYSTEM INTEGRATION (SII) 847 - 852 2474-2317 2017 

  The swarm of birds and fish produces the well organized behavior even though each individual is only interacting with neighbors. In order to form the swarm, there should be some rules that each individual is following. In this paper, we examine whether the neural network can learn the individual behavioral rules and reproduce the swarm behavior. In the experiment, boids swarm and real fish swarm are used for the target of learning and reproduction. As a result, the neural network could learn and reproduce the behavior almost perfectly for the boids swarm, and partially for the real fish swarm.
• Robustness of Mobile Robot Localization using Recurrent Convolutional Neural Network

  Izuho Suginaka, Hiroyuki Iizuka, Masahito Yamamoto

  2017 21ST ASIA PACIFIC SYMPOSIUM ON INTELLIGENT AND EVOLUTIONARY SYSTEMS (IES) 95 - 100 2017 

  Mobile robot localization has been considered to be an important task in the field of robotics research. It is known that it is difficult to estimate the self-position in dynamic environments where the positions of objects used as landmarks change. In this paper, we propose a robust method to estimate self-position from the first person view captured by a camera on a robot using Recurrent Convolutional Neural Networks (RCNN), which is a neural network model that has a convolutional architecture known as CNN with recurrent nodes. The RCNN receives images and directly estimates the positions of the robot. Our proposed method is evaluated in simulated environments. Our experiments show that RCNN model can estimate the self position of the robot with high accuracy even if some objects move to different positions, that is, it has a robustness against objects obstructing visibility.
• Reproduction of swarm behavior by learning individual rules using neural network.

  Yosuke Nakamoto, Hiroyuki Iizuka, Masahito Yamamoto

  847 - 852 2017
• The development of spatial recognition and navigation in hierarchical recurrent neural network with convolution processing.

  Wataru Noguchi, Hiroyuki Iizuka, Masahito Yamamoto

  324 - 331 2017
• Increasing Stability of Human Interaction Against Time Delay on Perceptual Crossing Experiment

  Sohtaroh Saitoh, Hiroyuki Iizuka, Masahito Yamamoto

  INTELLIGENT AND EVOLUTIONARY SYSTEMS, IES 2016 8 361 - 369 2363-6084 2017 [Refereed][Not invited]
   

  Perceptual Crossing experiment is the method for analyzing human interaction with low degrees of freedom of perception and motion. In this experiment, participants need to establish a cooperative interaction to achieve a task. In this study, we introduce time delays of participant's perception in this experiment, and evaluate the stability of human social interaction against the time delay. Our result shows that human social interactions have the stability against the time delays by changing their behaviors adaptively. We also investigate if the stability can be enhanced by modulating the participant's behavior conversely. It is shown that it is possible to increase the stability of social interaction by slowing down behaviors of participants.
• Intuitive control of mobile robots, an architecture for autonomous adaptive dynamic behaviour integration

  Christos Melidis, Hiroyuki Iizuka, Davide Marocco

  Cognitive Processing 1 - 20 2017 [Refereed][Not invited]
  
• Evolution of Swarm Formation Using Homogeneous Multi-Robots

  Naohiro Shibuya, Hiroyuki Iizuka, Masahito Yamamoto

  Proceedings of The 2nd International Symposium on Swarm Behavior and Bio-Inspired Robotics 128 - 133 2017 [Refereed][Not invited]
  
• Establishing interaction between machine and medaka using deep Q-Network

  Ryo Nishimura, Hiroyuki Iizuka, Masahito Yamamoto

  BICT 2015 - 9th EAI International Conference on Bio-Inspired Information and Communications Technologies 16 (9) e3  2016/05/24 [Refereed][Not invited]
   

  Social interaction is the basic ability for animals to survive. It is difficult for a machine to interact with human or other animals because it is not clear how the machine should interact. This paper examines whether an artificial dot controlled by a machine can interact with a medaka and induce a desired behavior. The dot is displayed on a monitor. We use deep Q network (DQN) to learn how to move the dot. As a result, the DQN could learn some basic elements to interact with the medaka and the desired behavior could be induced.
• Mutual Learning Interface using the Segmentation of Actons

  Saitoh Kentaro, Iizuka Hiroyuki, Yamamoto Masahito

  Proceedings of JSPE Semestrial Meeting 公益社団法人 精密工学会 2016 575 - 576 2016 

  ロボットの構造が複雑になるにつれて，操縦するためのインタフェースも複雑なものとなり，ユーザは複雑な操縦方法の学習を強いられる．本研究では人間の学習負荷が低い簡易なインタフェースにもかかわらず，複雑な構造のロボットを操縦できるインタフェースの作成手法を提案する．動作の分節化を利用して複数のインタフェースを切り替えて学習を行うことで，さまざまな動作を可能とするインタフェースを構築し評価する．
• Proceedings in Adaptation, Learning and Optimization.

  Sohtaroh Saitoh, Hiroyuki Iizuka, Masahito Yamamoto

  361 - 369 2016
• Twist-State Classifier for Floating Marine Biomass Based on Physical Simulation

  Jun Ogawa, Hiroyuki Iizuka, Masahito Yamamoto, Masashi Furukawa

  INTELLIGENT AUTONOMOUS SYSTEMS 13 302 821 - 830 2194-5357 2016 [Refereed][Not invited]
   

  This paper describes new approaches for classifying twist of seaweeds. There are no evaluation measures of the twist formation of complicated objects quantitatively because the definition of a qualitative twist is a difficult problem. The twist of seaweeds is one of these problems. In this paper, we propose three factors (physical, geometric, and time factor of twist) for characterizing the twist state, and we develop the twist-state classifier based on these factors. Additionally, the analysis experiment verifies how the classifier shows the classification accuracy of twist state.
• Particle Swarm Optimization with Tour Representation for Solving Traveling Salesman Problems

  HONJO Masaya, IIZUKA Hiroyuki, YAMAMOTO Masahito, FURUKAWA Masashi

  Journal of Japan Society for Fuzzy Theory and Intelligent Informatics 日本知能情報ファジィ学会 28 (4) 744 - 755 1347-7986 2016 [Refereed][Not invited]
   

  In this paper, we propose a new Traveling Salesman Problem (TSP) solver based on Particle Swarm Optimization (PSO) Algorithm. PSO is one of the optimization methods classified into swarm intelligence, and consists of particles. Particles interact and move through solution space to find a better solution. PSO can find a good solution in a short time compared with Genetic Algorithm (GA) in many real-valued optimization problems. Because TSP is a combinatorial optimization problem, we change two points of the original PSO for solving TSP. The first point is that the position of each particle is represented by a tour instead of a vector. The second is that particles move by using Insertion method. Insertion method is an operation to combine a tour and sub-paths of other two tour. We analyze relation between parameters and length of an obtained tour, and indicate a guide to adjust parameters. The performance comparison result shows that the proposed method can find a better solution than Simulated Annealing (SA) and GA.
• Detecting Collapsed Buildings using Convolutional Neural Network for Estimating the Disaster Debris Amount

  利根川 凛, 飯塚 博幸, 山本 雅人, 古川 正志, 大内 東

  情報処理学会論文誌 57 (6) 1565 - 1575 1882-7764 2016 [Refereed][Not invited]
   

  津波の被害に代表される大規模な家屋の倒壊が起こる災害時において，被災状況を把握できずに起きる復旧の遅延が問題となっている．津波により建造物の倒壊が起こり大量のがれきが発生すると，早急に輸送手段や仮置き場の位置や数の手配が必要になる．しかしながら，現状では被災地での被害状況の把握，被災がれき量の推定について短時間で行う手法は確立されていない．本研究では，震災後に撮影される被災地の空撮画像を複数用い，被災地の地図情報から家屋のある範囲を抽出し，畳み込みニューラルネットワークによる学習から，家屋倒壊判別を行う．結果として，東日本大震災で被災地となった10地域の空撮画像を利用し，約86%の正答率を得た．また，使用地域の中で，テストデータの判別正答率の悪かった地域のみをテストデータに絞った場合でも判別を行い，前実験の結果と比較して，より多くの地域，および，条件の画像データを用意すれば，判別器の正答率が向上する可能性を示した．When a massive earthquake that causes Tsunami happens, it is too difficult to get a full picture of the damages caused by the disaster and it causes the delay to recover from it. The debris generated by Tsunami or broken houses block roads and all transportation for people, rescue supply and bringing debris stop. In order to remove the debris and clear the roads, we need to decide which and how many spaces should be allocated for temporal storages immediately. However, there is no method to estimate the amount of generated debris and to get a full picture of the damage for a short time. This paper proposes a novel method that uses a convolutional neural network to classify images taken by a plane into damage or no-damage automatically. The network is trained with the images of 10 different areas stricken by the Great East Japan Earthquake. Our results shows that the trained network can correctly answer with about 86% and we found that the correct rates changes in response to the extents of the damages in different areas. The possibility to create a better network classifier is discussed in the end.
• A novel approach to quantitative evaluation of tangle formations for seaweeds in stirrer cultivation

  Jun Ogawa, Hiroyuki Iizuka, Masahito Yamamoto, Masashi Furukawa

  Journal of Robotics and Mechatronics 28 (1) 40 - 49 1883-8049 2016 [Refereed][Not invited]
   

  We discuss novel approaches to the control of seaweed tangle formations in stirrer cultivation. Cultivating seaweed is one important way to avoid such formation. Because defining such formation is difficult based on human recognition alone, there is currently no quantitative evaluation criterion for formation. We develop physical simulation for analyzing formations in a water flow field and model three factors – physical, geometric and time – for characterizing formations. Our criterion is that formations are created by using these factors as input to a nonlinear support vector machine. To show the effectiveness of our simulation and criteria, we confirm the control effects of the water flow in simulation and the real world. Results show that our simulation model is useful for avoiding such formation in the real world.
• Proposing Multimodal Integration Model Using LSTM and Autoencoder

  Wataru Noguchi, Hiroyuki Iizuka, Masahito Yamamoto

  EAI Endorsed Transactions on Security and Safety 16 (10) e1 - 1 2016 [Refereed][Not invited]
  
• 不確定性を含むデジタルカーリングにおけるゲーム木探索

  加藤修, 飯塚博幸, 山本雅人

  情報処理学会論文誌ジャーナル 57 (11) 2354 - 2364 2016 [Refereed][Not invited]
  
• Proposing storage location assignment using self-organizing map on network topology

  Kenichi Minami, Hiroyuki Iizuka, Masashi Furukawa, Masahito Yamamoto

  Transactions of the Japanese Society for Artificial Intelligence 30 (6) 737 - 744 1346-8030 2015/10/27 [Refereed][Not invited]
   

  The distribution center became more important because the growth of the internet enabled us to buy various products easily on the Internet. In the distribution center, one of the main works is order picking which is to carry the products from shelves of the warehouse according to the orders received from customers. Efficient order picking reduces the large amount of work and the improvement of the order picking is necessary in a larger distribution center. It is important for order picking not only to give workers a good tour plan but also to assign products to the storage shelves in the distribution center. It is known that it is effective to consider frequency order and frequency of co-occurrence at the same time for storage location assignment. The conventional studies proposes the class-based method for frequency order and evaluation function to evaluate frequency order and co-occurrence of orders at the same time. This study proposes a novel method how to assign products to the storage using a co-occurrence network of ordered products and self-organizing map on network topology of the warehouse. Our proposed method is compared with the conventional studies and our experiments show that our proposed method can be more effective than the conventional methods.
• Developing evaluation function of hex using board network characteristics and SVM

  Takada Kei, Honjo Masaya, Iizuka Hiroyuki, Yamamoto Masahito

  Transactions of the Japanese Society for Artificial Intelligence 30 (6) 729 - 736 1346-8030 2015/10/27 [Refereed][Not invited]
   

  The game of Hex is the board game with simple rules and is classified as a two-player, zero-sum, logical perfect information game. The game proceeds by putting their pieces in turn on empty cells of the board. A player wins if the player connects the two opposing sides of the board with their own color pieces. Our previous study clarified that it is effective to develop a computer Hex strategies with the network characteristics as the evaluation function to evaluate the board states from the global and local perspectives and showed that there is the best parameter to decide the ratio between global and local evaluation during a match. In order to go beyond the strategy, we hypothesize that the ratio must change during a match depending on the board states as human players differently evaluate the board states at the beginning, middle and final stages. First, we examine the hypothesis whether the better wining rate can be achieved by changing the ratio of global and local evaluation and propose a novel computer Hex program that can evaluate the board states while changing the global and local evaluation by recognizing the board states with SVM. Our proposed method is evaluated with the current world-champion program called MoHex.
• Time delay effect on social interaction dynamics

  Hiroyuki Iizuka, Sohtaroh Saitoh, Davide Marocco, Masahito Yamamoto

  HAI 2015 - Proceedings of the 3rd International Conference on Human-Agent Interaction 217 - 219 2015/10/21 [Refereed][Not invited]
   

  This paper investigates time-delay effects of the human social interaction to understand how human can adapt to the time delay, which will be required in software agents to establish a harmonic interaction with human. We performed the minimal experiments of social interaction called perceptual crossing experiments with time delay. Our result shows that the social interaction breaks down when the total amount of time delay is given more than about one second. However, the interaction breaks more easily when the time delay is given to both participants than to either participant.
• Water Flow Control for Inhibiting Seaweed Twist in Real Environment and Physical Simulation

  Jun Ogawa, Hiroyuki Iizuka, Masahito Yamamoto, Masashi Furukawa

  Proceedings of the Twentieth International Symposium on Artificial Life and Robotics (AROB 20th 2015) 291 - 296 2015/10 [Refereed][Not invited]
  
• Four-pole galvanic vestibular stimulation causes body sway about three axes

  Kazuma Aoyama, Hiroyuki Iizuka, Hideyuki Ando, Taro Maeda

  SCIENTIFIC REPORTS 5 10168  2045-2322 2015/05 [Refereed][Not invited]
   

  Galvanic vestibular stimulation (GVS) can be applied to induce the feeling of directional virtual head motion by stimulating the vestibular organs electrically. Conventional studies used a two-pole GVS, in which electrodes are placed behind each ear, or a three-pole GVS, in which an additional electrode is placed on the forehead. These stimulation methods can be used to induce virtual head roll and pitch motions when a subject is looking upright. Here, we proved our hypothesis that there are current paths between the forehead and mastoids in the head and show that our invented GVS system using four electrodes succeeded in inducing directional virtual head motion around three perpendicular axes containing yaw rotation by applying different current patterns. Our novel method produced subjective virtual head yaw motions and evoked yaw rotational body sway in participants. These results support the existence of three isolated current paths located between the mastoids, and between the left and right mastoids and the forehead. Our findings show that by using these current paths, the generation of an additional virtual head yaw motion is possible.
• Application of local clustering organization to reactive job-shop scheduling

  Yasumasa Tamura, Hiroyuki Iizuka, Masahito Yamamoto, Masashi Furukawa

  SOFT COMPUTING 19 (4) 891 - 899 1432-7643 2015/04 [Refereed][Not invited]
   

  This study focuses on the reactive scheduling in manufacturing systems. In practical situations, the predetermined schedule often changes under the influence of the unpredictable or variable environment in the factory. The reactive scheduling (RS) is a methodology to modify the predetermined schedule to cope with variable situations without suspending the proceeding of the processes on the schedule. Therefore, the RS requires a method to improve the schedule with fast computational time. To obtain an effective method for the RS, this paper proposes a novel RS method using local clustering organization. Also, this paper examines its effectiveness by a numerical experiment. Our results suggest that the proposed method is more effective than the method using genetic algorithm.
• ミニマックス法に基づく報酬伝搬を用いたモンテカルロ木探索法

  三橋 允, 飯塚 博幸, 山本 雅人

  精密工学会学術講演会講演論文集 公益社団法人 精密工学会 2015 755 - 756 2015 

  ゲーム木探索の中でもランダムなシミュレーションを繰り返すことで近似的な評価値を得るモンテカルロ木探索法と呼ばれる手法が存在する。しかしランダム性故に現実にはまず起こり得ないシミュレーション結果も評価に含まれてしまうことがあるため、数手に渡り正確な読みが必要となる局面は苦手とされている。そこでシミュレーション結果（報酬）をミニマックス的に伝搬することで、末端の情報を活用し評価精度の向上を目指す。
• 畳み込みニューラルネットワークを用いた群行動の分類

  遠峰 孝太, 飯塚 博幸, 山本 雅人

  精密工学会学術講演会講演論文集 公益社団法人 精密工学会 2015 923 - 924 2015 

  群で生活する動物は蟻や魚等，数多く存在する．種により群の形態は様々であるが，同じ種の群の違いは一見するとわかりにくい．本研究では，群の全体的な振る舞いの違いが機械学習によって分類可能かどうかを検証する．分類器には，画像認識において高い成果を得ている畳み込みニューラルネットワークを動画が扱えるように拡張したものを用いて動画データから群のパターンの違いを識別することが有用であるかを検証する．
• ゲーム木探索に基づくカーリングAIの開発

  加藤 修, 飯塚 博幸, 山本 雅人

  精密工学会学術講演会講演論文集 公益社団法人 精密工学会 2015 915 - 916 2015 

  カーリングは氷上のチェスと呼ばれる戦略性の高いゲームである．また，確率的要素を持ち，取り得る手と局面が無限に存在するゲームの研究材料として注目されている．近年，カーリングシミュレータが開発され，カーリングの戦略を解析することが可能となった．本研究では，実際の試合における時間的制約を考慮したゲーム木探索に基づくカーリングAIを開発し，その有効性をシミュレーションにより検証する．
• Extended Local Clustering Organization with Rule-Based Neighborhood Search for Job-shop Scheduling Problem

  Yasumasa Tamura, Hiroyuki Iizuka, Masahito Yamamoto

  PROCEEDINGS OF THE 18TH ASIA PACIFIC SYMPOSIUM ON INTELLIGENT AND EVOLUTIONARY SYSTEMS, VOL 2 465 - 477 2015 [Refereed][Not invited]
   

  Job-shop scheduling problem(JSP) is one of the hardest combinatorial optimization problems. Local clustering organization (LCO) is proposed by Furukawa et al. to solve such a combinatorial optimization problems as the metaheuristic algorithm. Its effectiveness for the JSP is verified by the comparison with genetic algorithm. However, since LCO is based on the greedy search, the solution is often trapped in local minima. To improve the problem, this study proposes a novel neighborhood search method using priority rules. This paper also shows the extended LCO integrated with the search method.
• Digital Curling Strategy based on Game Tree Search

  Masahito Yamamoto, Shu Kato, Hiroyuki Iizuka

  2015 IEEE CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND GAMES (CIG) 474 - 480 2325-4270 2015 [Refereed][Not invited]
   

  Strategy for digital curling based on the game tree search is demonstrated. Digital curling has been developed for simulating curling which is one of the winter sports. We present a curling playing program run on the digital curling simulator. It enable us to decide the direction and the speed of the stone to be delivered for maximizing the evaluation values of resultant game states. The novel evaluation function is constructed and the effective method for reducing the simulation trials is proposed for finding the best shot on the current game state. Our experimental results reveal that our proposed program outperforms the previous rule-based program and competes with the MonteCarlo based program.
• Developing Computer Hex Using Global and Local Evaluation Based on Board Network Characteristics

  Kei Takada, Masaya Honjo, Hiroyuki Iizuka, Masahito Yamamoto

  ADVANCES IN COMPUTER GAMES, ACG 2015 9525 235 - 246 0302-9743 2015 [Refereed][Not invited]
   

  The game of Hex was invented in the 1940s, and many studies have proposed ideas that led to the development of a computer Hex. One of the main approaches developing computer Hex is using an evaluation function of the electric circuit model. However, such a function evaluates the board states only from one perspective. Consequently, it is recently defeated by the Monte Carlo Tree Search approaches. In this paper, we therefore propose a novel evaluation function that uses network characteristics to capture features of the board states from two perspectives. Our proposed evaluation function separately evaluates the board network and the shortest path network using betweenness centrality, and combines the results of these evaluations. Furthermore, our proposed method involves changing the ratio between global and local evaluations through a support vector machine (SVM). So, it yields an improved strategy for Hex. Our method is called Ezo. It was tested against the world-champion Hex program MoHex. The results showed that our method was superior to the 2011 version of MoHex on an 11 x 11 board.
• Modeling the enlargement effect of countergcurrent stimulation on sway evoked by galvanic vestibular stimulation

  青山一真, 青山一真, 飯塚博幸, 櫻井悟, 宮本靖久, 古川正紘, 古川正紘, 前田太郎, 前田太郎, 安藤英由樹, 安藤英由樹

  日本バーチャルリアリティ学会論文誌 20 (4) 291 - 298 1344-011X 2015 [Refereed][Not invited]
  
• Priority rule-based construction procedure combined with genetic algorithm for flexible job-shop scheduling problem

  Soichiro Yokoyama, Hiroyuki Iizuka, Masahito Yamamoto

  Journal of Advanced Computational Intelligence and Intelligent Informatics 19 (6) 892 - 899 1883-8014 2015 [Refereed][Not invited]
   

  The heuristic method we propose solves the flexible job-shop scheduling problem (FJSP) using a solution construction procedure with priority rules. FJSP is more complex than classical scheduling problems in that operations are processed on one of multiple candidate machines, one of which must be selected to get a feasible solution. The solution construction procedure with priority rules is implemented on top of the efficient existing method for solving the FJSP which consists of a genetic algorithm and a local search method. The performance of the proposed method is analyzed using various benchmark problems and it is confirmed that our proposed method outperforms the existing method on problems with particular conditions. The conditions are further investigated by applying the proposed method on newly created benchmark.
• Applying homeostatic neural controller to multi-legged robot and adaptivity to novel disruptions

  Iizuka, H, Nakai, H, Yamamoto, M

  Proceedings of the European Conference on Artificial Life 264 - 270 2015 [Refereed][Not invited]
  
• Attraction basin sphere estimating genetic algorithm for neuroevolution problems

  Zhuoran Xu, Hiroyuki Iizuka, Masahito Yamamoto

  Artificial Life and Robotics 19 (4) 317 - 327 1614-7456 2014/12/10 [Refereed][Not invited]
   

  In our previous work, we proposed a niching genetic algorithm: attraction basin sphere estimating genetic algorithm (ABSEGA). It can detect and recognize attraction basin spheres on a fitness landscape. Attraction basin spheres are used to improve the performance of niching. However, ABSEGA does not work well on Neuroevolution problems, because those problems are usually high dimensional and have numerous local optima. In this paper, we calculate the height of valleys to improve the niching results. The height is used to determine if an optimum is important, so we can track important optima even among hundreds of unimportant optima. We examine our method in a robotic arm problem, in which we evolve an artificial neural network to control the arm to catch balls. The results show that our method has a high ability to escape local optima and find relatively better solutions.
• Unconscious learning of auditory discrimination using mismatch negativity (MMN) neurofeedback

  Ming Chang, Hiroyuki Iizuka, Yasushi Naruse, Hideyuki Ando, Taro Maeda

  SCIENTIFIC REPORTS 4 6729  2045-2322 2014/10 [Refereed][Not invited]
   

  Neurofeedback is a strong direct training method for brain function, wherein brain activity patterns are measured and displayed as feedback, and trainees try to stabilize the feedback signal onto certain desirable states to regulate their own mental states. Here, we introduce a novel neurofeedback method, using the mismatch negativity (MMN) responses elicited by similar sounds that cannot be consciously discriminated. Through neurofeedback training, without participants' attention to the auditory stimuli or awareness of what was to be learned, we found that the participants could unconsciously achieve a significant improvement in the auditory discrimination of the applied stimuli. Our method has great potential to provide effortless auditory perceptual training. Based on this method, participants do not need to make an effort to discriminate auditory stimuli, and can choose tasks of interest without boredom due to training. In particular, it could be used to train people to recognize speech sounds that do not exist in their native language and thereby facilitate foreign language learning.
• Using minimal human-computer interfaces for studying the interactive development of social awareness

  Tom Froese, Hiroyuki Iizuka, Takashi Ikegami

  FRONTIERS IN PSYCHOLOGY 5 1061  1664-1078 2014/09 [Refereed][Not invited]
   

  According to the enactive approach to cognitive science, perception is essentially a skillful engagement with the world. Learning how to engage via a human-computer interface (HCI) can therefore be taken as an instance of developing a new mode of experiencing. Similarly, social perception is theorized to be primarily constituted by skillful engagement between people, which implies that it is possible to investigate the origins and development of social awareness using multi-user HCIs. We analyzed the trial-by-trial objective and subjective changes in sociality that took place during a perceptual crossing experiment in which embodied interaction between pairs of adults was mediated over a minimalist haptic HCI. Since that study required participants to implicitly relearn how to mutually engage so as to perceive each other's presence, we hypothesized that there would be indications that the initial developmental stages of social awareness were recapitulated. Preliminary results reveal that, despite the lack of explicit feedback about task performance, there was a trend for the clarity of social awareness to increase over time. We discuss the methodological challenges involved in evaluating whether this trend was characterized by distinct developmental stages of objective behavior and subjective experience.
• Alternating images of congruent and incongruent movement creates the illusion of agency

  Takumi Yokosaka, Hiroyuki Iizuka, Tomoko Yonemura, Daisuke Kondo, Hideyuki Ando, Taro Maeda

  SCIENTIFIC REPORTS 4 6201  2045-2322 2014/08 [Refereed][Not invited]
   

  We report a novel illusion whereby people perceive both congruent and incongruent hand motions as a united, single, and continuous motion of one's own hand (i.e. a sense of agency). This arises when individuals watch congruent and incongruent hand motions alternately from a first person perspective. Despite an individual knowing that s/he is not performing the motion, this illusion still can arise. Although a sense of agency might require congruency between predicted and actual movements, united motion is incongruent with predicted movement because the motion contains oscillating movement which results from switching hand movement images. This illusion offers new insights into the integration mechanism of predicted and observed movements on agency judgment. We investigated this illusion from a subjective experience point of view and from a motion response point of view.
• Hybrid Genetic Algorithm with Priority Rule-based Reconstruction for Flexible Job-shop Scheduling

  Soichiro Yokoyama, Hiroyuki Iizuka, Masahito Yamamoto

  2014 JOINT 7TH INTERNATIONAL CONFERENCE ON SOFT COMPUTING AND INTELLIGENT SYSTEMS (SCIS) AND 15TH INTERNATIONAL SYMPOSIUM ON ADVANCED INTELLIGENT SYSTEMS (ISIS) 749 - 754 2377-6870 2014 [Refereed][Not invited]
   

  A heuristic method for solving flexible job-shop scheduling problem (FJSP) is proposed. FJSP is more complex than classical scheduling problems in that operations are processed on one of multiple candidate machines and one of them must be selected to obtain a feasible solution. The proposed method utilizes a solution improvement procedure with priority rules. This procedure is implemented on top of the efficient existing method for the FJSP which consists of genetic algorithm and local search method. The performance of the proposed method is analyzed on various benchmark problems. As a result, it is confirmed that the proposed method outperforms the existing method on problems with particular conditions while its average performance does not match the state-of-the-art algorithm.
• Insertion-based Particle Swarm Optimization with Local Interaction

  Masaya Honjo, Hiroyuki Iizuka, Masahito Yamamoto

  2014 JOINT 7TH INTERNATIONAL CONFERENCE ON SOFT COMPUTING AND INTELLIGENT SYSTEMS (SCIS) AND 15TH INTERNATIONAL SYMPOSIUM ON ADVANCED INTELLIGENT SYSTEMS (ISIS) 755 - 760 2377-6870 2014 [Refereed][Not invited]
   

  Insertion-based Particle Swarm Optimization (IPSO) is an optimization method for Traveling Salesman Problem (TSP) s. IPSO can find a better solution in a short time compared with Simulated Annealing (SA) and Genetic Algorithm (GA). In order to find a near optimal solution, we propose IPSOLB by improving IPSO. IPSOLB is based on the local version of PSO. In this method, a particle is affected by its neighbor particles instead of the whole population. As a result of this modification, agents are not converged immediately on the best solution obtained so far, and the population maintains various candidate solutions. For this reason, in comparison with IPSO, IPSOLB can be expected to search a solution while avoiding local optimum solutions. Through numerical experiments, it is shown that the proposed method can find a better solution than IPSO in reasonable time.
• Swarm Behavior of Simulated Flapping Birds using Kuramoto Model

  Ryota Kato, Hiroyuki Iizuka, Masahito Yamamoto

  2014 IEEE/SICE INTERNATIONAL SYMPOSIUM ON SYSTEM INTEGRATION (SII) 112 - 117 2014 [Refereed][Not invited]
   

  This paper shows the different types of swarm behaviors of simulated flapping birds obtained in our simulation. The individual birds are modeled in the physical virtual environment and flying by flapping. The evolutionary method is applied to obtain how to fly as an individual. After the evolution, the multiple birds interact with each other with Kuramoto model while flying at the same time. Our result shows the top-down regulation from the shape of formations to the individual behaviors. The regulation changes individual objectives to the globally determined objectives due to the entrainment caused by Kuramoto model.
• An interface for unconscious learning using mismatch negativity neurofeedback

  Ming Chang, Hiroyuki Iizuka, Yasushi Naruse, Hideyuki Ando, Taro Maeda

  ACM International Conference Proceeding Series 28:1-28:2  2014 [Refereed][Not invited]
   

  There are a lot of skills that it takes time for us to learn in our life. To be precise, it is not clear what and how to learn. For example, one of the biggest problems in the language learning is that learners cannot recognize novel sounds that do not exist in their native language, and it is difficult to gain a listening ability for these novel sounds [1]. Here, we developed a novel neurofeedback (NF) method, using the mismatch negativity (MMN) responses elicited by similar sounds, that can help people to unconsciously improve their auditory perceptual skills. In our method, the strength of the participants' MMN as a measure of perceptual discriminability is presented as visual feedback to provide a continuous, not binary, cue for learning. We found evidence that significant performance improvement for behavioral auditory discrimination and neurophysiological measure occurs unconsciously. Based on our findings, the method has great potential to provide effortless auditory perceptual training and develop an unconscious learning interface device.
• An interface for unconscious learning using mismatch negativity neurofeedback

  Ming Chang, Hiroyuki Iizuka, Yasushi Naruse, Hideyuki Ando, Taro Maeda

  ACM International Conference Proceeding Series 109 - 112 2014 [Refereed][Not invited]
   

  There are a lot of skills that it takes time for us to learn in our life. To be precise, it is not clear what and how to learn. For example, one of the biggest problems in the language learning is that learners cannot recognize novel sounds that do not exist in their native language, and it is difficult to gain a listening ability for these novel sounds [1]. Here, we developed a novel neurofeedback (NF) method, using the mismatch negativity (MMN) responses elicited by similar sounds, that can help people to unconsciously improve their auditory perceptual skills. In our method, the strength of the participants' MMN as a measure of perceptual discriminability is presented as visual feedback to provide a continuous, not binary, cue for learning. We found evidence that significant performance improvement for behavioral auditory discrimination and neurophysiological measure occurs unconsciously. Based on our findings, the method has great potential to provide effortless auditory perceptual training and develop an unconscious learning interface device.
• Priority rule-based reconstruction for total weighted tardiness minimization of job-shop scheduling problem

  Soichiro Yokoyama, Hiroyuki Iizuka, Masahito Yamamoto

  JOURNAL OF ADVANCED MECHANICAL DESIGN SYSTEMS AND MANUFACTURING 8 (5) JAMDSM0073  1881-3054 2014 [Refereed][Not invited]
   

  We propose an efficient heuristic method for job-shop scheduling problems (JSP) with the objective of total weighted tardiness minimization The proposed method uses schedule reconstructions by priority rules to guide a local search towards promising solutions. Typically priority rules determine the whole schedule and thus incorporating it with local search procedure is difficult. In our proposed method, a priority rule decides a schedule within an arbitrary selected time window and the rest of the schedule is determined by the schedule obtained by a conventional local search method. The priority rule is given by a linear combination of simple priority rules. To improve a schedule efficiently, an appropriate set of time window and gains of the linear combined priority rule is required. Therefore, we optimize the set of time window and rule gains with genetic algorithm This rule-based reconstruction procedure and the conventional local search procedure are alternately applied to a current solution. In the experiments, the efficiency of rule-based reconstruction procedure is verified and the proposed method is compared with one of the most effective existing methods. The results show that the proposed method outperforms the existing method on large problems with sufficient computational time. The average performance is particularly improved due to the ability of rule-based reconstruction procedure to escape from local optima of the conventional local search procedure efficiently.
• ネットワーク指標を用いたコンピュータ Hex 戦略の開発

  高田圭, 本庄将也, 飯塚博幸, 山本雅人

  情報処理学会論文誌 55 (11) 2421 - 2430 2014 [Refereed][Not invited]
  
• Enhancement effect of countecurrent using dead current strength in Galvanic Vestibular Stimulation(VR/AR penetrating into service fields and daily lives)

  Aoyama Kazuma, Ando Hideyuki, Iizuka Hiroyuki, Maeda Taro

  Transactions of the Virtual Reality Society of Japan 特定非営利活動法人 日本バーチャルリアリティ学会 19 (3) 315 - 318 1344-011X 2014 [Refereed][Not invited]
   

  In this work, we researched the human perceptual attribution for acceleration sensation evoked by Galvanic Vestibular Stimulation (GVS) and validated the enhancement effect of countercurrent using the dead current strength. In the results of experiments, we searched that the current threshold is 0.3 - 0.4mA by measuring the rate of correct directional perception. To validate the enhancement effect of countercurrent, we compared the rate of correct perception in long and short countercurrent and constant current. In the result, the rate of correct directional perception in long countercurrent is significantly higher than that of constant current in the dead current value.
• Embodied social interaction constitutes social cognition in pairs of humans: A minimalist virtual reality experiment

  Tom Froese, Hiroyuki Iizuka, Takashi Ikegami

  SCIENTIFIC REPORTS 4 3672  2045-2322 2014/01 [Refereed][Not invited]
   

  Scientists have traditionally limited the mechanisms of social cognition to one brain, but recent approaches claim that interaction also realizes cognitive work. Experiments under constrained virtual settings revealed that interaction dynamics implicitly guide social cognition. Here we show that embodied social interaction can be constitutive of agency detection and of experiencing another's presence. Pairs of participants moved their "avatars"' along an invisible virtual line and could make haptic contact with three identical objects, two of which embodied the other's motions, but only one, the other's avatar, also embodied the other's contact sensor and thereby enabled responsive interaction. Co-regulated interactions were significantly correlated with identifications of the other's avatar and reports of the clearest awareness of the other's presence. These results challenge folk psychological notions about the boundaries of mind, but make sense from evolutionary and developmental perspectives: an extendible mind can offload cognitive work into its environment.
• 複雑系アプローチによる他者の認識とコミュニケーションの創発

  飯塚博幸

  計測と制御 53 (9) 821 - 827 2014 [Not refereed][Invited]
  
• Learning Effect of Laparoscopy Training System using View-Sharing Technology and Verification for Practical Use(VR for Medicine, Welfare, and Healthcare)

  KONDO Daisuke, IIZUKA Hiroyuki, ANDO Hideyuki, OBAMA Kazutaka, SAKAI Yoshiharu, MAEDA Taro

  Transactions of the Virtual Reality Society of Japan 日本バーチャルリアリティ学会 18 (4) 487 - 496 1344-011X 2013/12/31 [Not refereed][Not invited]
   

  We propose a novel training method for laparoscopy using view-sharing technology where the expert's skillful movements are superimposed on the learner's view. When learning the skill, the learner just traces the expert's movement as if they feel the skillful movements as their own. Our proposed method was evaluated in terms of time required for the task and the number of errors. The training effect was also tested with the doctors in training and the acquired skills were evaluated by the expert surgeon.
• Investigating Extended Embodiment Using a Computational Model and Human Experimentation

  Yuki Sato, Hiroyuki Iizuka, Takashi Ikegami

  CONSTRUCTIVIST FOUNDATIONS 9 (1) 73 - + 1782-348X 2013/11 [Refereed][Not invited]
   

  Context . Our body schema is not restricted to biological body boundaries (such as the skin), as can be seen in the use of a cane by a person who is visually impaired or the "rubber hands" experiment. The tool becomes a part of the body schema when the focus of our attention is shifted from the tool to the task to be performed. Problem . A body schema is formed through interactions among brain, body, tool, and environment. Nevertheless, the dynamic mechanisms underlying changes in the body schema are still not fully understood. Method . To study the changing conditions of the body schema (e.g., a shift of attention), a simulation model of object discrimination was extended to differentiate between two kinds of sensitivities - sensitivity to an object being directly manipulated and sensitivity to another object being manipulated by the first. The proposed model consisted of windmills with different numbers of vanes. A model agent was required to determine the number of vanes on a windmill by touching the vanes blindly with an arm controlled by a neural network. Placing a second windmill beside the first and gearing the two windmills to move associatively resulted in the agent using the first windmill as a tool with which to discern the number of vanes on the second windmill. In other words, an agent's body schema can shift from its arm tip to the boundary between the first and second windmills. We then introduced an experiment with a real windmill model to test the hypothesis demonstrated by the theoretical model. Results . We demonstrated that even simple computational agents can have two different sensitivities to the windmills. One agent becomes sensitive to the first windmill and insensitive to the second one. Another agent becomes insensitive to the first windmill and sensitive to the second one by using the first one as a tool. Therefore, we concluded that the boundary of the body schema was extended to the first windmill in the case of the latter agent because paying attention to the task to be performed instead of the tool itself is essential for the tool to be considered as part of the body schema. Analysis of the experiments using a computational model and human experimentation revealed that a shift from an irregular to a regular movement of a windmill is an indication of extension of the body schema. Constructivist content . Our insights are beneficial for enactive cognitive science. This is because an extended body schema questions the Cartesian separation between subject and object, and the self and the environment.
• Extended homeostatic adaptation model with metabolic causation in plasticity mechanismtoward constructing a dynamic neural network model for mental imagery

  Hiroyuki Iizuka, Hideyuki Ando, Taro Maeda

  ADAPTIVE BEHAVIOR 21 (4) 263 - 273 1059-7123 2013/08 [Refereed][Not invited]
   

  This study presents an extended dynamic neural network model of homeostatic adaptation as the first step toward constructing a model of mental imagery. In the homeostatic adaptation model, higher-level dynamics internally self-organized from sensorimotor dynamics are associated with desired behaviors. These dynamics are regenerated when drastic changes occur, which might break the internal dynamics. Due to the weak link between desired behavior and internal homeostasis in the original homeostatic adaptation model, adaptivity is limited. In this paper, we improve on the homeostatic adaptation model to create a stronger link between desired behavior and internal homeostasis by introducing a metabolic causation in a plasticity mechanism and show that it becomes more adaptive. Our results show that our model has three different time scales in the adaptive behaviors, which are discussed with our cognition and mental imagery.
• Investigating Segmentation of Continuous Motion in Memorizing using CNV-like Potentials(Psychology, Measurement of Brain Function and VR)

  Sunagawa Mika, Niwa Masataka, Iizuka Hiroyuki, Ando Hideyuki, Maeda Taro

  Transactions of the Virtual Reality Society of Japan 日本バーチャルリアリティ学会 18 (1) 45 - 54 1344-011X 2013/03/31 [Not refereed][Not invited]
   

  This study aimed at investigating if CNV-Iike variations are elicited in Electroencephalograms (EEG) when people remember human continuous motion. It is known that there are some important postures in continuous human motion, and the segments divided by the significant postures attract human attention. Since the situation is similar to Event-related brain potential (ERP) experiments, we expected that brain wave variations like Contingent Negative Variation (CNV) would also be elicited during motion remembering. In this study, we found that negative variations tend to precede segments divided by manually selected significant postures.
• Countercurrent enhances acceleration sensation in galvanic vestibular stimulation.

  Kazuma Aoyama, Hiroyuki Iizuka, Hideyuki Ando, Taro Maeda

  23rd International Conference on Artificial Reality and Telexistence, ICAT 2013, Tokyo, Japan, December 11-13, 2013 IEEE Computer Society 116 - 121 2013 [Refereed][Not invited]
  
• Poster: Head Motion Transmission Based on Center of Rotation

  Daisuke Kondo, Hiroyuki Iizuka, Hideyuki Ando, Taro Maeda

  2013 IEEE SYMPOSIUM ON 3D USER INTERFACES (3DUI) 145 - 146 2013 [Refereed][Not invited]
   

  We propose a novel method to navigate one's head rotation and position when two persons perform cooperative work with wearing head-mounted display, which is called view-sharing system. It is necessary to synchronize and match their head motions between two persons. In this system, the head motion is transmitted and guided by the target-maker shown in the user's view. In a conventional method, the partner's head position was shown in the view as target marker. In this paper, the marker was modified in terms of two typical human motion patterns; changing point of view by moving one's head around the target object, and changing one's gaze point by turning the head. Our proposed method was evaluated with the head tracking task and showed the effectiveness.
• Detecting CNV-like variation when remembering and generating continuous motion

  Hiroyuki Iizuka, Mika Sunagawa, Masataka Niwa, Hideyuki Ando, Taro Maeda

  2013 IEEE VIRTUAL REALITY CONFERENCE (VR) 1087-8270 2013 [Refereed][Not invited]
   

  Our aim of this study is to investigate the possibility of estimating interruptibility from Electroencephalograms (EEG). We focus on contingent negative variation which is elicited in response to concentration. Our results support that our method could correctly detects the user's internal states such as just watching or actively remembering even the external situations were completely same and also CNV is elicited when controlling continuous motion.
• Experimental study on co-evolution of categorical perception and communication systems in humans

  Hiroyuki Iizuka, Davide Marocco, Hideyuki Ando, Taro Maeda

  Psychological Research 77 (1) 53 - 63 0340-0727 2013/01 [Refereed][Not invited]
   

  In this paper, we present an experiment that integrates a semiotic investigation with a dynamical perspective on embodied social interactions. The primary objective is to study the emergence of a communication system between two interacting individuals, where no dedicated communication modalities are predefined and the only possible interaction is very simple, non-directional, and embodied. Throughout the experiment, we observe the following three phenomena: (1) the spontaneous emergence of turn-taking behaviour that allows communication in non-directional environments (2) the development of an association between behaviours and perceptive categories (3) the acquisition of novel meaning by exploiting the notion of complementary set theory. © 2012 Springer-Verlag.
• Basic Study of Supporting Ocular Movements by Galvanic Vestibular Stimulation

  Hashimoto Yuki, Sugisaki Aru, Yonemura Tomoko, Iizuka Hiroyuki, Ando Hideyuki, Maeda Taro

  Transactions of the Virtual Reality Society of Japan 日本バーチャルリアリティ学会 17 (1) 23 - 32 1344-011X 2012/03/31 [Not refereed][Not invited]
   

  Galvanic vestibular stimulation is known to cause ocular movement. However, the effects of GVS on ocular movements have only been investigated when gazing at a certain point, despite the fact that humans use two different strategies to follow moving targets: saccade and smooth pursuit. The effects of GVS may be different for these two strategies. This paper investigates the effects of GVS during saccade and smooth pursuit. The results show that GVS exerts different effects on each of these eye movement strategies.
• Tumori Control : Manipulate Robot with detection and transmission of an Archetype of Behavioral Intention

  Niwa Masataka, Iizuka Hiroyuki, Ando Hideyuki, Maeda Taro

  Transactions of the Virtual Reality Society of Japan 日本バーチャルリアリティ学会 17 (1) 3 - 10 1344-011X 2012/03/31 [Not refereed][Not invited]
   

  We propose novel architecture to realize a low-degree of freedom (DOF) Tsumori controller to manipulate a high-DOF robot. We believe that humans can immerse themselves to manipulate a robot if the robot reflects user intention. In our Tsumori controller, the user intuitively operates a joystick, and the robot moves semi -autonomously and reflects the user's intention that is extracted from intuitive input sequences. In this paper, we explain how to extract Tsumori, which is an archetype of human behavioral intention, and how to realize a Tsumori controller.
• Optimization for Inducing Multi-Degree of Freedom Motion by Information Presentation of One Degree of Freedom

  Yoshito Kumakura, Yuki Hashimoto, Daisuke Kondo, Hiroyuki Iizuka, Hideyuki Ando, Taro Maeda

  2012 IEEE/SICE INTERNATIONAL SYMPOSIUM ON SYSTEM INTEGRATION (SII) 410 - 415 2012 [Refereed][Not invited]
   

  When human exercises multi-degrees of freedom (DOF) motion, they just pay attention to only part of the body motion and can control the whole body motion. By consciously adjusting low-DOF movements, it is possible to induce multi-DOF motion, which is referred as a "knack" in the sport. Acquiring knacks can drastically improve multi-DOF motor skills by low-DOF information presentation, and it is also used in motor learning. We consider that "knack" is "what induces multi-DOF motion by low-DOF information presentation" and "what improves motor skills". In this study, we investigated whether multi-DOF motion can be induced by single-DOF information presentation, that is sound frequency, and whether motor skills are improved through our human experiments.
• Turn-taking Supports Humanlikeness and Communication in Perceptual Crossing Experiments - Toward developing human-like communicable interface devices

  Hiroyuki Iizuka, Davide Marocco, Hideyuki Ando, Taro Maeda

  IEEE VIRTUAL REALITY CONFERENCE 2012 PROCEEDINGS 1 - 4 2012 [Refereed][Not invited]
   

  Our aim of this paper is to investigate the human communication in terms of two following questions. One is how human can know the fact that an interacting partner is human. Another is how non-communicative behaviour can become communicative. To answer these questions, we performed two experiments exploiting the idea of perceptual crossing experiments. As a result, we will show that the turn-taking structure supports humanlikeness and human communication in the primitive non-verbal interaction. Our results will be discussed with ambient interface technology.
• Pseudo-attraction Force Display Using Vibrating Motors - Design of asymmetric oscillation for generating an illusion of being pulled

  Hidenori Hamaguchi, Masataka Niwa, Hiroyuki Iizuka, Hideyuki Ando, Taro Maeda

  IEEE VIRTUAL REALITY CONFERENCE 2012 PROCEEDINGS 1 - 2 2012 [Refereed][Not invited]
   

  We developed a new pseudo-attraction force display using four vibrating motors. The advantage of this device is that it uses phase difference control to alter the time width of pulses to generate asymmetric oscillation. It does not require altering the frequency of the vibrating motors. In this study, we investigated the influence of the pulse width generated in the device using vibrating motors on the perceptive intensity of pseudo-attraction force. From the result, the oscillation having shorter pulse widths within the range of 10-20 ms induced the "being-pulled" sensation more strongly.
• A video see-through face mounted display for view sharing

  Yuki Hashimoto, Daisuke Kondo, Tomoko Yonemura, Hiroyuki Iizuka, Hideyuki Ando, Taro Maeda

  ACM SIGGRAPH 2012 Posters, SIGGRAPH'12 115  2012 [Refereed][Not invited]
  
• Effects of observed motion speed on segmenting behavioral intention

  Hideyuki Ando, Masataka Niwa, Hiroyuki Iizuka, Taro Maeda

  Proceedings - IEEE International Workshop on Robot and Human Interactive Communication 304 - 307 2012 [Refereed][Not invited]
   

  When training for dance or sports, amateurs observe and mimic the physical exertion of experts to acquire skill by observing others. However, humans don't memorize consecutive operations, but instead make discrete divisions and memorize body movements. The posture that becomes a key from consecutive operations is removed and memorized for discretion in a process we call segmentation. The movement is reproduced by smooth interpolations between the clause and the clause memorized as segmentation. In the first experiment, we clarified the existence of this segmentation by showing video of smooth movements to participants who selected the segment/frame that became a key. We confirmed commonness in this segment selection. In experiment 2, to reflect the physical exertion that made the segmentation, the participants input force to force sensors by a control stick. We showed video of smooth movements to them and simultaneously input the force pattern that corresponds to the movement. The force pattern, which uniformly converges by such repetition, is different depending on each participant. We call this method the extraction of segmented behavioral intention. On the other hand, we can arbitrarily change the speed of the physical exertion by expanding and contracting the segments of the movement video that obtained the force pattern by extraction of segmented behavioral intention. Since the expanded and contracted pattern range at a certain speed even when the movement speed changed, we preserved the shape and the selected segments. However, the segment shape changes when the movement speed is constantly fast. © 2012 IEEE.
• Co-creativity of communication system on behavioral interaction

  Hiroyuki Iizuka, Hideyuki Ando, Taro Maeda, Davide Marocco

  Proceedings - IEEE International Workshop on Robot and Human Interactive Communication 298 - 303 2012 [Refereed][Not invited]
   

  This study presents an experiment that integrates a semiotic investigation with a dynamical perspective on embodied social interactions. The primary objective is to study co-creativity of a communication system on the human-human nonverbal interaction. Throughout the experiment, the results of established communication system on uni- and bi-directional interactions are compared. Finally, the role of co-creativity in the evolution of communication systems will be discussed. © 2012 IEEE.
• Emergence of Communication and Turn-taking Behavior in Nonverbal Interaction

  IIZUKA Hiroyuki, ANDO Hideyuki, MAEDA Taro

  The Transactions of the Institute of Electronics, Information and Communication Engineers. A 一般社団法人電子情報通信学会 95 (1) 165 - 174 0913-5707 2012/01/01 [Not refereed][Not invited]
   

  人と人工システムの調和的な相互作用の成立を目指し,本論文では人同士が行う相互行為からなるコミュニケーションに焦点を当てる.言語コミュニケーションを含む日常の人同士の相互作用は多くのモダリティを含み,解析が困難なものとなり,かつ,我々が日常使っているために多くの先入観を含み対象として適さない.そのため,相互作用を簡単な身体の運動と知覚に十分に制限し,2者間においてあらかじめ意味が与えられていない身体的相互作用からコミュニケーションが成立していく過程を調べることによって,人同士のコミュニケーションの背後にある身体的相互作用のダイナミクスを明らかにする.実験では,相手が人かどうかを判断することだけを目的にしているにもかかわらず,人の言語コミュニケーションに見られる時間的役割の転換であるターンテイキングが,身体的相互作用に創発することを示す.
• Identification of factors related to occurrence of "Shikkuri" Feeling at Pitching

  Hashimoto Yuki, Kumakura Yoshito, Yonemura Tomoko, Iizuka Hiroyuki, Ando Hideyuki, Maeda Taro

  Transactions of the Virtual Reality Society of Japan 日本バーチャルリアリティ学会 16 (4) 633 - 641 1344-011X 2011/12/31 [Not refereed][Not invited]
   

  We sometimes experience a positive feeling during playing sports/exercising without knowing the consequences of the motions. The feeling is called "Shikkuri", which is an onomatopoeia in Japanese which is considered an important feeling when learning motion skills. Some coaches already use this onomatopoeia in motion skill training. However it is not clear at all how and when the feeling arises. Our aim is to clarify the mechanism of the feeling and to exploit the feeling for teaching motion skills. As the first step toward our goal, we identify the factors related to perception of the Shikkuri feeling in the case of pitching.
• Effects of CPR training using the view sharing system

  Yonemura Tomoko, Hashimoto Yuki, Kondo Daisuke, Niwa Masataka, Iizuka Hiroyuki, Ando Hideyuki, Maeda Taro

  Transactions of the Virtual Reality Society of Japan 日本バーチャルリアリティ学会 16 (4) 623 - 632 1344-011X 2011/12/31 [Not refereed][Not invited]
   

  This paper investigates the learning effects of the Cardio Pulmonary Resuscitation (CPR) using the view-sharing system that can blend the views from the first person perspective of the instructor and the learner. The usual way of learning the CPR procedures is watching the video of instructor's action recorded from the third person perspective and trying CPR. However, there are difficulties for learners in the third person perspective video to recognize where the trainer pays attention and what he/she checks. Therefore, we clarify how the first person perspective helps for learning of CPR. As a result, we found that learners wearing our view-sharing system make better performances than the conventional method and can easily recognize their mistakes of procedures. We discuss about effects of skill training using the first person perspective by the view-sharing system.
• Fingernail-mounted Display of Attraction Force and Texture

  Niwa Masataka, Hamaguchi Hidenori, Iizuka Hiroyuki, Maeda Taro, Ando Hideyuki

  Transactions of the Virtual Reality Society of Japan 日本バーチャルリアリティ学会 16 (3) 409 - 414 1344-011X 2011/09/30 [Not refereed][Not invited]
   

  The paper studies two methods of haptic. One is an attraction force display that can induce attraction force by a cyclic movement of a weight with asymmetric acceleration. Another is a texture display that induces a sensation of texture by giving off vibration while a subject traces a finger over a flat surface. In this paper, we propose a novel design that can induce both attraction force and texture feeling. The prototype consists of four vibration motors, which are controlled to generate asymmetric acceleration and vibration. The device is evaluated by experiments.
• A method to transmit tactile information by nail-mounted vibration for active touch

  Hashimoto Yuki, Yumura Takeshi, Yonemura Tomoko, Iizuka Hiroyuki, Maeda Taro, Ando Hideyuki

  Transactions of the Virtual Reality Society of Japan 日本バーチャルリアリティ学会 16 (3) 399 - 408 1344-011X 2011/09/30 [Not refereed][Not invited]
   

  We propose a method to transmit tactile information from one person to another using nail-mounted tactile display. Our proposed method conveys tactile information that is obtained by detecting the vibration on the nail of a sender when tracing a texture, and generates a vibration on the nail of a receiver to re-create the tactile perception while the subject tracing on a flat surface. In this paper, we reported about measuring method of tactile information, control method of actuator and developing a new actuator in order to share tactile perceptions with two people.
• Inducing human motion by visual manipulation

  Shin Okamoto, Hiroki Kawasaki, Hiroyuki Iizuka, Takumi Yokosaka, Tomoko Yonemura, Yuki Hashimoto, Hideyuki Ando, Taro Maeda

  ACM International Conference Proceeding Series 32  2011 [Refereed][Not invited]
   

  This paper reports a study of augmenting human motions by manipulating visual images displayed to users. The target motion is not only the motion that can be seen in the subject's views (i.e. hands or foots motion) but also the full-body motion that cannot be captured from their own perspective. As a result, it is shown that the motions are modulated without any physical contacts only by manipulated images. Copyright c 2011 ACM.
• Effective galvanic vestibular stimulation in synchronizing with ocular movement

  Aru Sugisaki, Yuki Hashimoto, Tomoko Yonemura, Hiroyuki Iizuka, Hideyuki Ando, Taro Maeda

  ACM International Conference Proceeding Series 28  2011 [Refereed][Not invited]
   

  It is known that galvanic vestibular stimulation can cause ocular movement. Our final goal is to use GVS to support ocular movements. However, the effects of GVS to ocular movements are basically investigated while gazing at a certain point despite the fact that we have two different strategies to follow a moving target such as saccade and smooth pursuit. The effect might be different because those two use different mechanism. Therefore, this paper investigates the GVS effects during saccade. As a result, we show that the effect of GVS depends on the timing when GVS is given after the target marker moves. Copyright © 2011 ACM.
• View sharing system for motion transmission

  Daisuke Kondo, Keitaro Kurosaki, Hiroyuki Iizuka, Hideyuki Ando, Taro Maeda

  ACM International Conference Proceeding Series 26  2011 [Refereed][Not invited]
   

  We are developing 'view sharing' system for supporting a remote corporative work. The view sharing is constructed from the video-see-through head mounted displays (VST-HMD) and motion trackers. This system allows two users in remote places to share their first-person views each other. The users can share what the other user is seeing, and furthermore the users can correspond their spatial perception, motion and head movement. By sharing those sensations, the non-verbal skills can be transmitted from skilled person to the non-skilled person. Using this system expert in remote place can instruct the non-skilled person to improve task performance. Copyright © 2011 ACM.
• Coordinated behavior between visually coupled dyads

  Hiroyuki Iizuka, Daisuke Kondo, Hiroki Kawasaki, Hideyuki Ando, Taro Maeda

  ACM International Conference Proceeding Series 23  2011 [Refereed][Not invited]
   

  We describe how visually coupled people start their synchronized behavior with two visual coupling conditions: view-swapping and view-blending. In the view-swapping condition, two people's views are changed from the first-person perspective so that both see their partner's views. The view-blending condition allows people to see the blended view of both views. We report the results of different coordinated strategies to start synchronization that is observed in different conditions. In terms of the time required to start synchronization, view-swapping outperforms view-blending. Copyright © 2011 ACM.
• Skill transmission for hand positioning task through view-sharing system

  Keitaro Kurosaki, Hiroki Kawasaki, Daisuke Kondo, Hiroyuki Iizuka, Hideyuki Ando, Taro Maeda

  ACM International Conference Proceeding Series 20  2011 [Refereed][Not invited]
   

  In this paper, we describe the skill transmission through our viewsharing system that can mix or exchange the first person perspectives from the exact the partner's viewpoints. Since a nonskilled person can see the first person perspective of a skilled person, the motion of the non-skilled person is intuitively modified and supported. The task for the skill transmission is to play theremin that requires precise hand motions. As a result we show that the skill transmission effectively happens with our view-sharing system compared with the conventional method, side-by-side teaching. The way of effective augmenting human ability will be discussed. Copyright © 2011 ACM.
• Parasitic Humanoid: The wearable robotics as a behavioral assist interface like oneness between horse and rider

  Taro Maeda, Hideyuki Ando, Hiroyuki Iizuka, Tomoko Yonemura, Daisuke Kondo, Masataka Niwa

  ACM International Conference Proceeding Series 18  2011 [Refereed][Not invited]
   

  The Parasitic Humanoid (PH) is a wearable robotic human interface for sampling, modeling, and assisting nonverbal human behavior. This anthropomorphic robot senses the behavior of the wearer and has the internal models to learn the process of human sensory motor integration, thereafter it begins to predict the next behavior of the wearer using the learned models. When the reliability of the prediction is sufficient, the PH outputs the difference from the actual behavior as a request for motion to the wearer by motion induction using sensory illusion. Through the symbiotic interaction, the internal model and the process of human sensory motor integration approximate each other asymptotically. This process is available to transmit modalities such as senses of sight, hearing, touch, force and balance with human embodiment. This synergistic multimodal communication between distant people wearing PH can realize experience-sharing, skill transmission, and human behavior supports. Copyright 2011 ACM.
• Bongard,J., The utility of evolving simulated robot morphology increases with task complexity for object manipulation(複雑な作業の実行には身体形状と身体制御の相互作用が鍵を握っている), J. of Artificial Life, Vol.16, Issue 3, MIT Press, 2010

  飯塚 博幸

  人工知能学会誌 社団法人人工知能学会 25 (5) 743 - 745 0912-8085 2010/09 [Not refereed][Invited]
  
• 2 Real-World-Oriented Interface Based on Embodiment(Recent Trends in Real-world Interface Systems)

  IIZUKA Hiroyuki, NIWA Masataka, KONDO Daisuke, ANDO Hideyuki, MAEDA Taro

  IPSJ Magazine 一般社団法人情報処理学会 51 (7) 767 - 774 0447-8053 2010/07 [Not refereed][Not invited]
   

  ユーザの身体性を考慮し，自然かつ直観的に感覚や意図を伝送するためのインタフェースを紹介する．本稿では，従来のインタフェースでは表現することの困難な空間知覚，運動感覚やスキル，意図を取り上げる．感覚を伝送するためには運動レベルでの作用が必要であり，いかにして運動に働きかけることのできるインタフェースを実現するかを解説する．また，ヒトの意図は直観的な振舞いにおける運動に現れるため，それを検出する手法について述べる．
• Collaboration and Skill Transmission by First-person Perspective View Sharing System

  Hiroki Kawasaki, Hiroyuki Iizuka, Shin Okamoto, Hideyuki Ando, Taro Maeda

  2010 IEEE RO-MAN 125 - 131 2010 [Refereed][Not invited]
   

  When two distant persons establish cooperative interaction, how to share their motions and sensations and how to adjust or revise their motions are important for cooperation. In this paper, we propose an approach for sharing first-person perspectives to establish collaboration and to transmit a skill from one to another. We developed a view-sharing system to realize such interaction. To investigate the fundamental behavioral property of humans with our system, we examined a simple collaborated behavior and found that a situation where subjects only see their partner's view improves velocity following. By exploiting this property, we transmitted the basic skill required for the Diabolo trick to non-skilled persons. Through our system, the performances of non-skilled persons with the assistance of a skilled person surpassed individual performances
• 超身体感覚

  前田 太朗, 安藤 英由樹, 飯塚 博幸

  日本バーチャルリアリティ学会誌 = Journal of the Virtual Reality Society of Japan 14 (2) 99 - 103 1342-6680 2009/06/30 [Not refereed][Not invited]
  
• Performance Evaluation of Recommendation Algorithms Based on Rating-recommendation Interaction

  山下 晃弘, 川村 秀憲, 飯塚 博幸

  情報処理学会論文誌 論文誌トランザクション 情報処理学会 2008 (2) 47 - 57 1882-7772 2009/04 [Not refereed][Not invited]
  
• Performance Evaluation of Recommendation Algorithms Based on Rating-recommendation Interaction

  Akihiro Yamashita, Hidenori Kawamura, Hiroyuki Iizuka, Azuma Ohuchi

  情報処理学会論文誌. 数理モデル化と応用 一般社団法人情報処理学会 2 (2) 47 - 57 0387-5806 2009/03/27 [Not refereed][Not invited]
   

  The problem of information overload spreading across the Internet has been causing serious inefficiency in browsing and searching for information. As a way to overcome the problem, the recommender systems are recently used in many E-commerce sites. Many algorithms have been proposed to improve the accuracy of recommendation based on user ratings. The relation between recommender systems and users is rather interactive in the sense that recommendations decides which items are recommended to users and the results of ratings by users will affect the next recommendations. However, conventional studies have not considered the interactive aspects so much. Therefore, our aim of this paper is to propose a new evaluation model using multiagent modeling where the recommender system and agents (as users) interacts with each other. The properties of typical recommendation algorithms such as user-based and itembased collaborative filtering will be analyzed with our proposed model. Our results also suggest the possibilities to propose a novel and effective recommendation algorithm.
• Cooperative control of multiple neural networks for an indoor blimp robot

  Hidenori Kawamura, Hiroyuki Iizuka, Toshihiko Takaya, Azuma Ohuchi

  Artificial Life and Robotics 13 (2) 504 - 507 1433-5298 2009 [Refereed][Not invited]
   

  We report on the cooperative control of multiple neural networks for an indoor blimp robot. In our research group, the indoor blimp robot has been studied to achieve various flying robot applications. The objective of this article is to propose a robust controller that can adapt to mechanical accidents such as the breakdown of propellers. In our proposed method, each propeller thrust is independently calculated by a small neural network. We confirm the advantage of the proposed method against the control by a single large neural network. © International Symposium on Artificial Life and Robotics (ISAROB). 2009.
• The Anticipation of Human Behavior Using "Parasitic Humanoid"

  Hiroyuki Iizuka, Hideyuki Ando, Taro Maeda

  HUMAN-COMPUTER INTERACTION, PT III 5612 284 - 293 0302-9743 2009 [Refereed][Not invited]
   

  This paper proposes the concept of Parasitic Humanoid (PH) that can realize a wearable robot to establish intuitive interactions with wearers rather than conventional counter-intuitive ways like key-typing. It requires a different paradigm or interface technology which is called behavioral or ambient interface that can harmonize human-environment interactions to naturally lead to a more suitable state with the integration of information science and biologically inspired technology. We re-examine the use of wearable computers or devices from the viewpoint of behavioral information. Then, a possible way to realize PH is shown as integrated wearable interface devices. In order that PH establishes the harmonic interaction with wearers, a mutually anticipated interaction between a computer and human is necessary. To establish the harmonic interaction, we investigate the social interaction by experiments of human interactions where inputs and outputs of subjects are restricted in a low dimension at the behavioral level. The results of experiments are discussed with the attractor superimposition. Finally, we will discuss integrated PH system for human supports.
• Wearable robotics as a behavioral assist interface like oneness between horse and rider

  Taro Maeda, Hideyuki Ando, Hiroyuki Iizuka

  ACM International Conference Proceeding Series 81 - 88 2009 [Refereed][Not invited]
   

  The Parasitic Humanoid (PH) is a wearable robot for modeling nonverbal human behavior. This anthropomorphic robot senses the behavior of the wearer and has the internal models to learn the process of human sensory motor integration, thereafter it begins to predict the next behavior of the wearer using the learned models. When the reliability of the prediction is sufficient, the PH outputs the errors from the actual behavior as a request for motion to the wearer. Through symbiotic interaction, the internal model and the process of human sensory motor integration approximate each other asymptotically. Copyright 2009 ACM.
• Simulation and implement of memory-based PID control for indoor blimp robot

  Yoshifumi Yamagata, Hidenori Kawamura, Azuma Ohuchi, Toshihiko Takaya, Hiroyuki Iizuka

  Proceedings of the 13th International Symposium on Artificial Life and Robotics, AROB 13th'08 151 - 154 2008 

  We report on simulation and implement of Memory-based PID control for indoor blimp robot. In the control of indoor blimp robot, it is known that the PID control is effective. However, it is necessary to adjust PID parameters dynamically, since the environment changes dynamically. We use Memory-based PID controller for PID parameter tuning. The method is that a set of the PID parameters and input/output data of the controlled object are stored in the data-base, and are used to calculate the PID parameters to control object. The results of experiments demonstrated the effectiveness of Memory-based PID control for indoor blimp robot. ©ISAROB 2008.
• Cooperative control of multiple neural networks for indoor blimp robot

  Ryouta Nishioka, Hidenori Kawamura, Azuma Ohuchi, Toshihiko Takaya, Hiroyuki Iizuka

  Proceedings of the 13th International Symposium on Artificial Life and Robotics, AROB 13th'08 131 - 134 2008 

  We report on cooperative control of multiple neural networks for indoor blimp robot. In our laboratory, the indoor blimp has been studied to achieve various applications. Our objective of this paper is to propose a robust controller that can adapt to mechanical accidents such as breakdown of propellers. In our proposal method, each propeller thrust is independently calculated by each small network. We confirm effectiveness of the proposed method compared to the method of calculating thrusts by a single large neural network on the simulator. ©ISAROB 2008.
• Turn-taking interaction as a Cooperative and Co-creative Process

  Takashi Ikegami, Hiroyuki Iizuka

  INFANT BEHAVIOR & DEVELOPMENT 30 (2) 278 - 288 0163-6383 2007/05 [Refereed][Not invited]
   

  In the present article, computer simulation of turn-taking interaction was studied and compared with psychological experiments such as the double TV experiment and synchronous imitation. By introducing the concepts of virtual agents, prediction error and adaptability, the simulation showed that turn-taking dynamics is a cooperative and co-creative process between two agents, which is in accordance with psychological findings. In particular, much attention is paid to styles of motion, as turn-taking with chaotic spatial pattern has developed to be sensitive to it. (c) 2007 Elsevier Inc. All rights reserved.
• Simulated turn-taking and development of styles of motion

  Takashi Ikegami, Hiroyuki Iizuka

  Imitation and Social Learning in Robots, Humans and Animals: Behavioural, Social and Communicative Dimensions 301 - 322 2007/01/01 [Refereed][Not invited]
   

  We introduce a simulation study designed to develop a “synthetic psychology” (Braitenberg, 1984). Instead of studying real human/animal behavior, we study autonomous behavior of mobile agents that have virtual sensors to “see” the world and move around with virtual “wheels.” The autonomous behavior is synthesized by the agent's internal dynamics, which evolve using a genetic algorithm. A purpose of synthetic psychology is to create a new concept in order to understand an essential psychological phenomenon. Therefore, the simulation framework has to use models sufficiently simple to analyze the behavior, but sufficiently complex to provide a theory to understand the psychological experiments. As an example of synthetic psychology, we describe a simulation study of turn-taking using coupled dynamical recognizers. Studying turn-taking phenomena in robot experiments (e.g. Brooks et al., 1999 Dautenhahn, 1999 Steels and Kaplan, 2001 Miyake et al., in press) stresses the importance of embodiment and situatedness. In particular, MIT AI Lab's well-designed face robot, Kismet (Kismet project, 2000), can make use of human social protocols to stimulate natural emotions and social responses in humans. Even conversational turn-taking is established with a human subject. To do this, Kismet relies on subtle cues of human expression and interaction dynamics. Dautenhahn et al. used a mobile robot and a small humanoid robot to investigate the use of robotic toys in therapy and education of children with autism (Dautenhahn et al., 2002 AuRoRA project, 2005). These robots engage in playing a game with autistic children to elicit turn-taking and imitation.
• Toward spinozist robotics: Exploring the minimal dynamics of Behavioral preference

  Hiroyuki Iizuka, Ezequiel A. Di Paolo

  ADAPTIVE BEHAVIOR 15 (4) 359 - 376 1059-7123 2007 [Refereed][Not invited]
   

  A preference is not located anywhere in the agent's cognitive architecture, but it is rather a constraining of behavior which is in turn shaped by behavior. Based on this idea, a minimal model of behavioral preference is proposed. A simulated mobile agent is modeled with a plastic neurocontroller, which holds two separate high dimensional homeostatic boxes in the space of neural dynamics. An evolutionary algorithm is used for creating a link between the boxes and the performance of two different phototactic behaviors. After evolution, the agent's performance exhibits some important aspects of behavioral preferences such as durability and transitions. This article demonstrates (1) the logical consistency of the multi-causal view by producing a case study of its viability and providing insights into its dynamical basis and (2) how durability and transitions arise through the mutual constraining of internal and external dynamics in the flow of alternating high and low susceptibility to environmental variations. Implications for modeling autonomy are discussed.
• Effect of the Number of Users and Bias of Users' Preference on Recommender Systems.

  Akihiro Yamashita, Hidenori Kawamura, Hiroyuki Iizuka, Azuma Ohuchi

  Intelligent Data Engineering and Automated Learning - IDEAL 2007(IDEAL) 1112 (1121) 1112 - 1121 2007 [Refereed][Not invited]
  
• Emergence of body image and dichotomy of sensory and motor activity

  Hiroyuki Iizuka, Takashi Ikegami

  AISB'05 Convention: Proceedings of the Symposium on Next Generation Approaches to Machine Consciousness: Imagination, Development, Intersubjectivity and Embodiment 104 - 109 2005 

  This paper reconsiders a boundary between an agent and its environment. The boundary between a simulated agent and its environment is convoluted in dynamic processes of sensory and motor devices. However the boundary is not a static but a dynamic interface. In order to study the dynamic property of the interface, the un-fixed sensory-motor distinction is introduced. Practically, a mobile arm passively or actively explores an object and attaining some discrimination tasks. We develop the discrimination ability by using a genetic algorithm. A conscious state towards an object is investigated with this framework.
• Simulating autonomous coupling in discrimination of light frequencies

  Hiroyuki Iizuka, Takashi Ikegami

  Connection Science 16 (4) 283 - 299 0954-0091 2004/12 [Refereed][Not invited]
   

  To study the interfacial complexity between an agent and its environment such as the adaptive selection aspects of sensory inputs, we propose a new coupling mechanism, called autonomous coupling, where an agent can spontaneously switch on or off its interaction with the environment. An oscillatory neural system with autonomous coupling sums the sensory inputs and initiates action selection via a sensorimotor coupling. An example task we designed to show dynamical categorization is the classification of light frequencies. An evolved agent selects specified light frequencies by approaching them and avoiding light of other frequencies. Dynamical categorization and active coupling are the key concepts for the understanding of situated and embodied cognitive functions.
• Adaptability and diversity in simulated turn-taking behavior

  Hiroyuki Iizuka, Takashi Ikegami

  Artificial Life 10 (4) 361 - 378 1064-5462 2004/09 [Refereed][Not invited]
   

  Turn-taking behavior is simulated in a coupled-agents system. Each agent is modeled as a mobile robot with two wheels. A recurrent neural network is used to produce the motor outputs and to hold the internal dynamics. Agents are developed to take turns on a two-dimensional arena by causing the network structures to evolve. Turn taking is established using either regular or chaotic behavior of the agents. It is found that chaotic turn takers are more sensitive in response to inputs from the other agent. Conversely, regular turn takers are comparatively robust against noisy inputs, owing to their restricted dynamics. From many observations, including turn taking with virtual agents, we claim that there is a complementary relationship between robustness and adaptability. Furthermore, by investigating the recoupling of agents from different GA generations, we report the emergence of a new turn-taking behavior. Potential for synthesizing a new form of interaction is another characteristic of chaotic turn takers. © 2004 Massachusetts Institute of Technology.
• Adaptive coupling and intersubjectivity in simulated turn-taking behaviour

  Hiroyuki Iizuka, Takashi Ikegami

  Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science) 2801 336 - 345 0302-9743 2003 

  Turn-taking behaviour is simulated with a coupled agents system. Each agent is modelled as a mobile robot with two wheels. A recurrent neural network is used to produce the motor outputs and to hold the internal dynamics. Agents are developed to take turns on a two dimensional arena by causing the network structures to evolve. Turn-taking is established using either regular or chaotic behaviour of the agents. It is found that chaotic turn-takers are more sensitive to the adaptive inputs from the other agent. On the other hand, regular turntakers are comparatively insensitive to noisy inputs due to their restricted dynamics. From various observations, including turn-taking with virtual agents, we claim that the chaotic turn-taking agents become less robust when coping with virtual agents but at the same time, those agents are more adaptable to each other than the regular turn-taking agents. All these findings are discussed and compared with Trevarthen's double monitor experiments.
• Harmony Team.

  Hiroyuki Iizuka, Masatoshi Hiramoto, Hidenori Kawamura, Masahito Yamamoto, Azuma Ohuchi

  RoboCup 2000: Robot Soccer World Cup IV Springer 449 - 452 2000 [Refereed][Not invited]
  
• Learning of words in negotiation between autonomous agents

  Hiroyuki Iizuka, Keiji Suzuki, Masahito Yamamoto, Azuma Ohuchi

  Proceedings of the IEEE International Conference on Systems, Man and Cybernetics 2 0884-3627 1999 

  One of the important behaviors of agents in agent-based simulations is a negotiation. We focus on the price negotiations where both players have opposing interests as one of the negotiations. In the conventional price negotiation model, the process consists of an alternate succession of offers and counter-offers with exchanging the desired prices directly. As extended price negotiation model, we propose the price negotiation model whose process consists of an alternate succession of offers of desired price and counter-offers of a virtual word. We propose the agents with a unified learning system who can acquire to distinguish words and use them to negotiate. As a result, we show that the proposed agents can reach an agreement in negotiations and they acquire the negotiation strategy in evolutionary process.

MISC

• 無意識に英語のリスニング能力を向上できるニューロフィードバック手法

  CHANG Ming, 飯塚博幸, 成瀬康, 古川正紘, 古川正紘, 安藤英由樹, 安藤英由樹, 前田太郎, 前田太郎  ヒューマンインタフェースシンポジウム論文集(CD-ROM)  2017-  2017
• 無意識などの言語化が困難な情報を伝えるヒューマンインタフェースを目指して 無意識的に言語音知覚能力の向上のためのニューロフィードバック手法

  常明, 飯塚博幸, 成瀬康, 古川正紘, 安藤英由樹, 前田太郎  ヒューマンインタフェース学会誌  19-  (1)  2017
• Stability of Social Interaction with Different Time Delay of Perception and Movement in Perceptual Crossing Experiment

  齋藤 宗太郎, 飯塚 博幸, 山本 雅人  知識ベースシステム研究会  107-  13  -18  2016/03/01
• Design of Ambient Intelligent System for Supporting Human's Natural Adaption(Cognitive Interaction Design)

  IMAI Michita, ONO Tetsuo, SHINOZAWA Kazuhiko, OSAWA Hirotaka, IIZUKA Hiroyuki, SUZURIKAWA Jun, Michita Imai, Tetsuo Ono, Kazuhiko Shinozawa, Hirotaka Osawa, Hiroyuki Iizuka, Jun Suzurikawa  Journal of the Japanese Society for Artificial Intelligence  31-  (1)  43  -49  2016/01/01
• 22aBS-10 Embodied dynamics for sensing other's presence

  Kojima H., Oka M., Iizuka H., Ikegami T.  Meeting Abstracts of the Physical Society of Japan  71-  3088  -3088  2016
• バルーンロボットにおけるニューラルネットワークを用いたPID制御

  永田紘也, 飯塚博幸, 山本雅人, 鈴木恵二, 川村秀憲  電気・情報関係学会北海道支部連合大会講演論文集(CD-ROM)  2016-  2016
• ニューラルネットワークを用いたバルーンロボット制御

  永田紘也, 飯塚博幸, 山本雅人, 鈴木恵二, 川村秀憲  情報処理学会研究報告(Web)  2016-  (ICS-184)  2016
• 人工ニューラルネットワークを用いた動的スケジューリング問題の解法

  横山想一郎, 飯塚博幸, 山本雅人  計測自動制御学会システムインテグレーション部門講演会(CD-ROM)  17th-  2016
• JSPに対するタブーサーチ法におけるタブーリストの長さと解探索性能の関係

  斎藤渉, 横山想一郎, 飯塚博幸, 山本雅人  計測自動制御学会システムインテグレーション部門講演会(CD-ROM)  17th-  2016
• F-017 A Look-ahead method for curling with the probabilistic aspects

  Kato Shu, Iizuka Hiroyuki, Yamamoto Masahito  情報科学技術フォーラム講演論文集  14-  (2)  313  -314  2015/08/24
• O-024 Automatic Detection of Collapsed Buildings using Image Analysis for Estimating Disaster Debris Amount

  Tonegawa Rin, Iizuka Hiroyuki, Yamamoto Masahito, Furukawa Masashi, Ohchi Azuma  情報科学技術フォーラム講演論文集  14-  (4)  479  -480  2015/08/24
• 1P1-G08 Occurrence of Rubber Hand Illusion by Asynchronous Stimulation using the Reversal of Temporal Order Judgment of Tactile Stimulation

  UCHINO Keisuke, IIZUKA Hiroyuki, YAMAMOTO Masahito  ロボティクス・メカトロニクス講演会講演概要集  2015-  "1P1  -G08(1)"-"1P1-G08(4)"  2015/05/17  

  Rubber Hand Illusion (RHI) is a phenomenon that a subject feels that a rubber hand (dummy hand) is their own when the rubber hand and the real hand are stroked synchronously and the subject receives the consistent sensory inputs between visual and tactile sensations. The consistent visuo-tactile sensation is a necessary condition for RHI, however we report that RHI can be induced by an asynchronous stimulations between visual and tactile sensations. In our experiments, the subject is required to cross their arms and given successive stimulations on their each hand. Our experiment is conducted in virtual environment. It is known that such stimulations cause the mis-temporal order judgment. Our results support that arm-crossing confuses the body image and the asynchronous stimulations can induce RHI.
• 2A1-M01 Analysis of AI that can Establish Human Interaction in Perceptual Crossing Experiment

  SAITOH Sohtaroh, IIZUKA Hiroyuki, YAMAMOTO Masahito  ロボティクス・メカトロニクス講演会講演概要集  2015-  "2A1  -M01(1)"-"2A1-M01(4)"  2015/05/17  

  Perceptual Crossing experiment has been proposed to analyse the human social interaction with low dimensional sensation and motion. The previous study shows that human subjects can distinguish the partner with the distracted moving objects by coordinated behaviors established in two. In order to investigate the coordinated behavior established by human subjects, we design different types of AI programs and test how those programs can interact with human subjects. Our result shows that the turn-taking type AI program is better to reproduce human social interaction.
• Development of Curling AI Program Considering the Probabilistic Features of the Strategy

  加藤 修, 飯塚 博幸, 山本 雅人  知識ベースシステム研究会  104-  7  -12  2015/03/01
• FAN-14-034 Investigation Effective Parameters for Storage Location Assignment Using Self-Organizing Map.

  MINAMI Kenichi, IIZUKA Hiroyuki, YAMAMOTO Masahito  FAN Symposium : Intelligent System Symposium-fuzzy, AI, neural network applications technologies  2014-  (24)  152  -155  2014/09/18
• FAN-14-022 Modeling of the bird group behavior using the Kuramoto model

  KATO Ryota, IIZUKA Hiroyuki, YAMAMOTO Masahito  FAN Symposium : Intelligent System Symposium-fuzzy, AI, neural network applications technologies  2014-  (24)  100  -103  2014/09/18
• FAN-14-048 Co-evolution of adaptive behavior and muscle structure using a musculo-skeletal model

  MATSUBAYASHI Ryohei, IIZUKA Hiroyuki, YAMAMOTO Masahito  FAN Symposium : Intelligent System Symposium-fuzzy, AI, neural network applications technologies  2014-  (24)  210  -213  2014/09/18
• A method for Unconscious Learning using Mismatch Negativity Neurofeedback on pitch discrimination

  常 明, 飯塚 博幸, 成瀬 康  日本バーチャルリアリティ学会大会論文集 Proceedings of the Virtual Reality Society of Japan, Annual Conference  19-  480  -483  2014/09/17  [Not refereed][Not invited]
  
• 1-D-6 割付け規則を用いた遺伝的局所探索によるJSPの解法(スケジューリング(2))

  田村 康将, 飯塚 博幸, 山本 雅人  日本オペレーションズ・リサーチ学会秋季研究発表会アブストラクト集  2014-  66  -67  2014/08/28
• 1-D-7 ジョブショップ問題の重み付き納期遅れ最小化に対する割付け規則を用いた近似解法の提案(スケジューリング(2))

  横山 想一郎, 飯塚 博幸, 山本 雅人  日本オペレーションズ・リサーチ学会秋季研究発表会アブストラクト集  2014-  68  -69  2014/08/28
• Co-creative User Interface Developed by Mutual Learning of Human and Machine

  Iizuka Hiroyuki, Saitoh Kentaro, Yamamoto Masahito  電子情報通信学会技術研究報告 = IEICE technical report : 信学技報  114-  (85)  17  -22  2014/06/16  

  The complexity of user interfaces is increasing as the complexity of robot structures becomes higher. This paper proposes a co-creative user interface that can easily control the complex-structured robots despite that the structure of an input device keeps simple. The user interface can be developed through both machine and human learning. The co-creation improves the interface and decreases the learning load of the users. The proposed method is evaluated in terms of controllability of the multi-legged robot. In the end, we discuss co-creation on the user interface.
• 1A1-L03 An Approximate Method based on Genetic Algorithm and Dispatching Rules for Job-shop Scheduling Problem(Evolution and Learning for Robotics)

  TAMURA Yasumasa, IIZUKA Hiroyuki, YAMAMOTO Masahito  ロボティクス・メカトロニクス講演会講演概要集  2014-  "1A1  -L03(1)"-"1A1-L03(4)"  2014/05/24  

  The job-shop scheduling problem (JSP) is one of the combinatorial optimizations and one of the most difficult order decision problems. Many approximate algorithms, which are heuristic methods or metaheuristics, are studied to solve JSP, because JSP is categorized into NP-hard problems. The application of the dispatching rules is known as a practical heuristic for JSP or many other scheduling problems. This study proposes an extended algorithm for JSP based on the genetic algorithm and a novel local search method using the dynamic dispatching rules. The extended algorithm searches for effective dispatching rules along with schedules according to the genetic algorithm. Also the schedules are partially modified by the rules in every generation. In order to verify the effectiveness of the proposed algorithm, this paper shows the result of numerical experiments.
• 1A1-K06 Characterizing the Twist of Seaweeds for Controlling the Water Flow(Evolution and Learning for Robotics)

  OGAWA Jun, IIZUKA Hiroyuki, YAMAMOTO Masahito, FURUKAWA Masashi  ロボティクス・メカトロニクス講演会講演概要集  2014-  "1A1  -K06(1)"-"1A1-K06(4)"  2014/05/24  

  Twist of seaweeds is one of the physical problems that disturb the growth of the seaweeds in the marine biomass cultivation. This study aims to evaluate the twist of seaweeds in a quantitative way. There is no computational model to simulate dynamics of the twist of seaweeds. In this study, we create the physical model of the seaweeds using physics simulation and the states between seaweed individuals are characterized with feature vectors, which is composed the physical, geometrical, and time factors. The measure of twist can be defined as the number of features and classifies a state between individuals into "twist state" or "non-twist state".
• Strategy of Hex using betweenness centrality in board network

  TAKADA Kei, HONJO Masaya, IIZUKA Hiroyuki, YAMAMOTO Masahito  IEICE technical report. Artificial intelligence and knowledge-based processing  113-  (459)  7  -12  2014/03/03  

  Hex is a simple board game for two players, but the game strategy becomes very complicated. It is known that all positions of Hex can be represented as two networks. The betweenness centrality in the networks is believed to be effective to evaluate the possible next moves as a Hex strategy, but it is not enough. The conventional studies showed that the shortest path between edges is also important. Therefore, we proposed the evaluation function that can evaluate the betweenness centrality and the shortest path at the same time. Our results of games with Hexy or UCT algorithms showed that the proposed method effectively evaluates the current situations of games with those mixed network indices and becomes stronger.
• ジョブショップ問題の重み付き納期遅れ最小化に対する割付け規則を用いた近似解法の提案

  横山想一郎, 飯塚博幸, 山本雅人  日本オペレーションズ・リサーチ学会秋季研究発表会アブストラクト集  2014-  2014
• JSPに対する部分的な割り付け規則の適用による局所探索法の提案

  横山想一郎, 飯塚博幸, 山本雅人  日本機械学会ロボティクス・メカトロニクス講演会講演論文集(CD-ROM)  2014-  2014
• Authors' Response: From Bodily Extension to Bodily Incorporation

  Yuki Sato, Hiroyuki Iizuka, Takashi Ikegami  CONSTRUCTIVIST FOUNDATIONS  9-  (1)  89  -90  2013/11
• OS-20 「私」の境界と意味の現れへの構成論的アプローチ(オーガナイズドセッション,<特集>2013年度人工知能学会全国大会(第27回))

  飯塚 博幸, 宇野 良子  人工知能学会誌  28-  (6)  950  -950  2013/11/01  [Not refereed][Not invited]
  
• A study on extended telexistence using mirrored whole-body avatar

  近藤 大祐, 飯塚 博幸, 安藤 英由樹  日本バーチャルリアリティ学会大会論文集 Proceedings of the Virtual Reality Society of Japan, Annual Conference  18-  285  -288  2013/09/18
• Modeling of teaching motion in skill transfer with sharing first person perspectives

  北尾 太嗣, 近藤 大祐, 飯塚 博幸  日本バーチャルリアリティ学会大会論文集 Proceedings of the Virtual Reality Society of Japan, Annual Conference  18-  347  -350  2013/09/18
• From synthetic modeling of social interaction to dynamic theories of brain-body-environment-body-brain systems

  Tom Froese, Hiroyuki Iizuka, Takashi Ikegami  BEHAVIORAL AND BRAIN SCIENCES  36-  (4)  420  -421  2013/08  [Not refereed][Not invited]
   

  Synthetic approaches to social interaction support the development of a second-person neuroscience. Agent-based models and psychological experiments can be related in a mutually informing manner. Models have the advantage of making the nonlinear brain-body-environment-body-brain system as a whole accessible to analysis by dynamical systems theory. We highlight some general principles of how social interaction can partially constitute an individual's behavior.
• 画像合成・切替を用いた腹腔鏡手術トレーニングシステムと評価手法の提案(コミュニケーション支援及びヒューマン情報処理一般)

  安藤 英由樹, 近藤 大祐, 飯塚 博幸, 小濱 和貴, 坂井 義治, 前田 太郎  電子情報通信学会技術研究報告. HCS, ヒューマンコミュニケーション基礎  113-  (72)  195  -200  2013/05/23  [Not refereed][Not invited]
   

  腹腔鏡下手術とは,腹腔にカメラと鉗子等を刺入して行う外科手術であり,開腹手術と比べて低侵襲性であるが,難易度が高く熟練医が不足していることが大きな問題である.従来のトレーニングツールはボックストレーナやシミュレータなどあるものの,模擬環境での繰り返し学習が中心で,どのように熟練者のスキルを学習させるかについては考慮されておらず,長期の学習時間を要する,悪い癖がつくなどの問題を抱えていた.そこで,我々は内視鏡外科手術は術野像がモニタによって同じ視野が「共有される」という特性を利用して,段階的な学習ステップに応じた,熟練者の適切かつスムースな動きを修練者の間で共有することで,非言語的なスキルのコミュニケーションを図り,効果的なトレーニングを行う手法を提案し,また効果的な評価方法について議論する.
• 画像合成・切替を用いた腹腔鏡手術トレーニングシステムと評価手法の提案(コミュニケーション支援及びヒューマン情報処理一般)

  安藤 英由樹, 近藤 大祐, 飯塚 博幸, 小濱 和貴, 坂井 義治, 前田 太郎  電子情報通信学会技術研究報告. HIP, ヒューマン情報処理  113-  (73)  195  -200  2013/05/23  [Not refereed][Not invited]
   

  腹腔鏡下手術とは,腹腔にカメラと鉗子等を刺入して行う外科手術であり,開腹手術と比べて低侵襲性であるが,難易度が高く熟練医が不足していることが大きな問題である.従来のトレーニングツールはボックストレーナやシミュレータなどあるものの,模擬環境での繰り返し学習が中心で,どのように熟練者のスキルを学習させるかについては考慮されておらず,長期の学習時間を要する,悪い癖がつくなどの問題を抱えていた.そこで,我々は内視鏡外科手術は術野像がモニタによって同じ視野が「共有される」という特性を利用して,段階的な学習ステップに応じた,熟練者の適切かつスムースな動きを修練者の間で共有することで,非言語的なスキルのコミュニケーションを図り,効果的なトレーニングを行う手法を提案し,また効果的な評価方法について議論する.
• 1A2-C05 Learning Support using Self-Other Motion Overlapping for Laparoscopy Training(Medical Robotics and Mechatronics (2))

  KONDO Daisuke, IIZUKA Hiroyuki, ANDO Hideyuki, OBAMA Kazutaka, SAKAI Yoshiharu, MAEDA Taro  ロボティクス・メカトロニクス講演会講演概要集  2013-  "1A2  -C05(1)"-"1A2-C05(4)"  2013/05/22  

  We are developing laparoscopy training system, by adding a video synthesize functions on the conventional training box. The video of the expert's motion is shown on the monitor and is overwrapped onto the user's own view. the user can trace the expert's motion with one's forceps to learn ideal procedures. Our proposed method was evaluated in terms of learning effectiveness.
• 2A1-F04 Real-time Extracting and Transmitting Behavioral Intentions for Tsumori-Controller(Cooperation between Human and Machine)

  IIZUKA Hiroyuki, SHIMOYAMA Tohma, NIWA Masataka, ANDO Hideyuki, Maeda Taro  ロボティクス・メカトロニクス講演会講演概要集  2013-  "2A1  -F04(1)"-"2A1-F04(4)"  2013/05/22  

  This paper investigates how to extract and transmit behavioral intentions of users from intuitive inputs of Tsumori controller. We performed two experiments. The first experiment clarified how much the robot can be delayed to start moving toward operator's input without losing operator's agency, the feeling that they are initiating the motion. The second experiment compared fundamental two real-time algorithms to select robot segmented motion and showed that the average method could be better to stabilize the operator's intuitive input. Our results are discussed in terms of agency and real-time operation for Tsumori controller.
• ストロボ照明下における自己上肢運動の随意性の変化(日本基礎心理学会第31回大会,大会発表要旨)

  米村 朋子, 横坂 拓巳, 近藤 大祐, 橋本 悠希, 飯塚 博幸, 安藤 英由樹, 前田 太郎  基礎心理学研究  31-  (2)  222  -222  2013/03/30  [Not refereed][Not invited]
  
• HAI Technology That Subconsciously Connects with Human(Special Issue on HAI That Moves Humans)

  Ando Hideyuki, Iizuka Hiroyuki  Journal of Japanese Society for Artificial Intelligence  28-  (2)  310  -317  2013/03/01  [Not refereed][Not invited]
  
• 3Dマルチスリットディスプレイにおけるオブジェクトの3次元移動知覚特性

  平原誠一郎, 飯塚博幸, 前田太郎, 渡邊淳司, 安藤英由樹  日本バーチャルリアリティ学会大会論文集(CD-ROM)  18th-  2013
• 実物体とのなぞりによって生じる指腹振動に基づいたフィードバック制御を用いた爪装着型触覚提示

  鳥居航, 近藤大祐, 飯塚博幸, 安藤英由樹, 前田太郎  日本バーチャルリアリティ学会大会論文集(CD-ROM)  18th-  2013
• なぞり動作時における振動刺激を用いた外形提示手法

  橋本悠希, 飯塚博幸, 安藤英由樹, 前田太郎  日本バーチャルリアリティ学会研究報告  18-  (TX01)  2013
• Recognition of Others and Emergence of Communication on Sensory-Substitutional Experiment

  飯塚 博幸, 安藤 英由樹, 前田 太郎  人工知能学会全国大会論文集  27-  1  -3  2013
• 画像合成・切替を用いた腹腔鏡手術トレーニングシステムと評価手法の提案 (第98回 ヒューマンインタフェース学会研究会 コミュニケーション支援および一般)

  安藤 英由樹, 近藤 大祐, 飯塚 博幸  ヒューマンインタフェース学会研究報告集  15-  195  -200  2013
• Emergence of leader/follower distinction in proto-linguistic communication

  UNO Ryoko, Iizuka Hiroyuki, Suzuki Keisuke  Technical report of IEICE. HCS  112-  (176)  55  -60  2012/08/11  [Not refereed][Not invited]
   

  本稿は,リーダー・フォロワーの分化を,私たちが行った二つの実験から考える.一つ目は計算機シミュレーションによる実験で,エージェント同士が「主体性」の確認のために役割分化のある運動が生まれる.二つ目は,人間の被験者のペアが新しい「言語」を用いてコミュニケーションを構造化するのを観察する実験である.コミュニケーションのトピックを予め与えていないため,被験者はトピックを模索するが,その際に役割分化が現れやすい.本稿では、言語コミュニケーションにおいて主体性の確認は、トピックの模索のような意味生成を通じて行われているのではないかと論じ,二つの実験から得たモデルに基づいて様々なコミュニケーションを分析する可能性を探る.
• 頭部到達運動時における自己運動の変化知覚 : 視覚手がかりの影響の検討(日本基礎心理学会第30回大会,大会発表要旨)

  米村 朋子, 岡本 信, 近藤 大祐, 橋本 悠希, 飯塚 博幸, 安藤 英由樹, 前田 太郎  基礎心理学研究  30-  (2)  234  -234  2012/03/31  [Not refereed][Not invited]
  
• 上腕運動時における視覚情報中の自他運動の知覚的融合(日本基礎心理学会第30回大会,大会発表要旨)

  横坂 拓巳, 米村 朋子, 近藤 大祐, 橋本 悠希, 飯塚 博幸, 安藤 英由樹, 前田 太郎  基礎心理学研究  30-  (2)  234  -234  2012/03/31  [Not refereed][Not invited]
  
• Modulating Sense of Agency by Manipulating Visual Information

  IIZUKA Hiroyuki, ANDO Hideyuki, MAEDA Taro  Technical report of IEICE. HIP  111-  (432)  15  -18  2012/02/02  [Not refereed][Not invited]
   

  The aim of the present paper is to clarify how the distinction of self (sense of agency, SOA) and other-produced behavior can be synthesized and recognized in multisensory integration as our cognitive processes. To address this issue, we use tickling paradigm that it is hard for us to tickle ourselves. In our hypothesis, integration of vision, proprioception, and motor commands forms the SOA and disintegration causes the breakdown the SOA, which causes the feeling of others, producing tickling sensation even by tickling oneself This hypothesis was tested.
• 視野共有システムにおける頭部追従マーカの改良

  近藤大祐, 近藤大祐, 米村朋子, 米村朋子, 橋本悠希, 飯塚博幸, 安藤英由樹, 前田太郎  日本バーチャルリアリティ学会大会論文集(CD-ROM)  17th-  2012
• スキル伝達における頭部運動の協調を実現する教示動作の分析

  北尾太嗣, 米村朋子, 米村朋子, 横坂拓巳, 近藤大祐, 近藤大祐, 橋本悠希, 飯塚博幸, 安藤英由樹, 前田太郎  日本バーチャルリアリティ学会大会論文集(CD-ROM)  17th-  2012
• 多極前庭電気刺激における動的な電流印加の影響

  青山一真, 橋本悠希, 近藤大祐, 米村朋子, 飯塚博幸, 安藤英由樹, 前田太郎  日本バーチャルリアリティ学会大会論文集(CD-ROM)  17th-  2012
• 爪上振動刺激デバイスによる外形提示のための振動波形設計

  橋本悠希, 橋本悠希, 近藤大祐, 米村朋子, 飯塚博幸, 安藤英由樹, 前田太郎  日本バーチャルリアリティ学会大会論文集(CD-ROM)  17th-  2012
• 擬似牽引力による運動誘導を用いた超音波プローブ操作体験アプリの開発

  濱口英典, 橋本悠希, 飯塚博幸, 安藤英由樹, 前田太郎  日本バーチャルリアリティ学会研究報告  17-  (HDC09)  2012
• 1P1-H11 The Behavioral Intention Caused by Two Types of Tumori Controllers(VR and Interface)

  Niwa Masataka, Okada Shinya, Azuma Kentaro, Iizuka Hiroyuki, Ando Hideyuki, Maeda Taro  ロボティクス・メカトロニクス講演会講演概要集  2011-  "1P1  -H11(1)"-"1P1-H11(4)"  2011/05/26  

  Exploiting the time-segmentation of action recognition and generation, we have proposed "Tumori" controller that realizes to manipulate a high-DOF (degree of freedom) robot with a low-DOF joystick controller while maintaining the user's intention depending on the time-segmentation. In this paper, the relation between behavior intention and two type of input device("Tumori" controller) is investigated.
• 1P1-H10 Tumori Control : Manipulate Robot with an Archetype of Behavioral Intention(VR and Interface)

  Niwa Masataka, Okada Shinya, Azuma Kentaro, Iizuka Hiroyuki, Ando Hideyuki, Maeda Taro  ロボティクス・メカトロニクス講演会講演概要集  2011-  "1P1  -H10(1)"-"1P1-H10(3)"  2011/05/26  

  We propose novel architecture to realize a low-degree of freedom (DOF) Tsumori controller to manipulate a high-DOF robot. We believe that humans can immerse themselves to manipulate a robot if the robot reflects user intention. In our Tsumori controller, the user intuitively operates a joystick, and the robot moves semi -autonomously and reflects the user's intention that is extracted from intuitive input sequences. In this paper, we explain how to extract Tsumori, which is an archetype of human behavioral intention, and how to realize a Tsumori controller.
• パラサイトヒューマンシステムによる感覚伝送・共有とその応用

  橋本悠希, 米村朋子, 近藤大祐, 飯塚博幸, 安藤英由樹, 前田太郎  横幹連合コンファレンス(CD-ROM)  4th-  2011
• 音の周波数変化が随意運動に与える影響

  熊倉祥人, 橋本悠希, 飯塚博幸, 安藤英由樹, 前田太郎  日本バーチャルリアリティ学会大会論文集(CD-ROM)  16th-  2011
• 擬似牽引力を提示する非対称振動の設計手法に関する研究

  浜口英典, 丹羽真隆, 飯塚博幸, 安藤英由樹, 前田太郎  日本バーチャルリアリティ学会大会論文集(CD-ROM)  16th-  2011
• 人から人へのテレイグジスタンスにおける触覚伝送・共有技術

  橋本悠希, 橋本悠希, 米村朋子, 米村朋子, 飯塚博幸, 飯塚博幸, 前田太郎, 前田太郎, 安藤英由樹, 安藤英由樹, 梶本裕之, 梶本裕之  日本感性工学会大会予稿集(CD-ROM)  13th-  2011
• 視野画像の空間周波数の部分的操作が頭部運動による視標追従に与える影響

  米村朋子, 米村朋子, 横坂拓巳, 近藤大祐, 橋本悠希, 橋本悠希, 飯塚博幸, 安藤英由樹, 前田太郎  基礎心理学研究  29-  (2)  2011
• Multi-modal communications system using Parasitic Humanoid Network : Synergistic work support system using common viewing device

  ANDO Hideyuki, IIZUKA Hiroyuki, YONEMURA Tomoko, MAEDA Taro  Technical report of IEICE. HCS  110-  (33)  137  -142  2010/05/06  [Not refereed][Not invited]
   

  In this paper, we propose parasitic-humanoid network system that realizes skill transmission between distant people sharing experiences. In order to realize it, an optical conjugate video see-through HMD is developed. The system is evaluated with the experiments of real-time/off-line skill transmissions. Finally, we discuss feasibility and optimizing parameters for the system.
• Multi-modal communications system using Parasitic Humanoid Network : Synergistic work support system using common viewing device

  ANDO Hideyuki, IIZUKA Hiroyuki, YONEMURA Tomoko, MAEDA Taro  Technical report of IEICE. HIP  110-  (34)  137  -142  2010/05/06  [Not refereed][Not invited]
   

  In this paper, we propose parasitic-humanoid network system that realizes skill transmission between distant people sharing experiences. In order to realize it, an optical conjugate video see-through HMD is developed. The system is evaluated with the experiments of real-time/off-line skill transmissions. Finally, we discuss feasibility and optimizing parameters for the system.
• 凹凸感に係わる指腹への刺激の要素特定

  湯村武士, 橋本悠希, 橋本悠希, 米村朋子, 米村朋子, 飯塚博幸, 飯塚博幸, 安藤英由樹, 安藤英由樹, 前田太郎, 前田太郎  日本バーチャルリアリティ学会大会論文集(CD-ROM)  15th-  2010
• 一人称視野共有によるスキル伝達・学習効果の評価

  黒崎敬太郎, 川崎宏記, 近藤大祐, 米村朋子, 米村朋子, 橋本悠希, 橋本悠希, 飯塚博幸, 安藤英由樹, 前田太郎  日本バーチャルリアリティ学会大会論文集(CD-ROM)  15th-  2010
• 投球における「しっくり感」と投球結果の相関関係についての検証

  熊倉祥人, 橋本悠希, 飯塚博幸, 安藤英由樹, 前田太郎  日本バーチャルリアリティ学会大会論文集(CD-ROM)  15th-  2010
• 空間周波数処理を用いた視点誘導手法

  横坂拓巳, 米村朋子, 米村朋子, 岡本信, 川崎宏記, 近藤大祐, 橋本悠希, 橋本悠希, 飯塚博幸, 安藤英由樹, 前田太郎  日本バーチャルリアリティ学会大会論文集(CD-ROM)  15th-  2010
• 「つもり」制御におけるロボットの動作履歴が操縦者の直観的入力に与える影響

  岡田慎矢, 坂口翔太, 丹羽真隆, 東健太郎, 飯塚博幸, 安藤英由樹, 前田太郎  日本バーチャルリアリティ学会大会論文集(CD-ROM)  15th-  2010
• 視野共有システムにおけるVST-HMDの広視野角化と画像安定化による空間認識への効果

  服部響, 黒崎敬太郎, 川崎宏記, 近藤大祐, 橋本悠希, 橋本悠希, 米村朋子, 米村朋子, 飯塚博幸, 安藤英由樹, 前田太郎  日本バーチャルリアリティ学会大会論文集(CD-ROM)  15th-  2010
• スマートフォンを用いた触覚情報の共有に関する研究

  橋本悠希, 雨宮智浩, 米村朋子, 飯塚博幸, 安藤英由樹, 前田太郎  日本バーチャルリアリティ学会大会論文集(CD-ROM)  15th-  2010
• 1A1-G14 Image Stabilization for View Shared Remote Cooperative Work

  KONDO Daisuke, KUROSAKI Keitaro, YONEMURA Tomoko, IIZUKA Hiroyuki, ANDO Hideyuki, MAEDA Taro  ロボティクス・メカトロニクス講演会講演概要集  2010-  "1A1  -G14(1)"-"1A1-G14(3)"  2010  

  We are developing a remote cooperative work system using a view sharing. The view sharing is constructed from the video-see-through head mounted displays (VST-HMD) and motion trackers. Using the system, the users can share the first-person views each other. The image stabilization method is implemented to correspond the optical flow to head movement.
• 1A1-G13 Collaboration and Skill Transmission by First-person Perspective View Sharing Method

  KAWASAKI Hiroki, OKAMOTO Shin, IIZUKA Hiroyuki, ANDO Hideyuki, MAEDA Taro  ロボティクス・メカトロニクス講演会講演概要集  2010-  "1A1  -G13(1)"-"1A1-G13(4)"  2010  

  When two distant persons establish coordination in the tele-existence environment, it is important how to share each other's motions and sensations, and how to adjust or revise their motions to cooperate. There are some studies in which they use a third-person view to share motions, and less studies with first-person view despite the fact that there are reports where first-person view plays an important role for ownership and bodyimage. Therefore, we propose a method to blend the mutual first person's views to establish coordination where the partner's view is superimposed onto his/her own view. In the blended views, each other's motion is seen in an equivalent viewpoint. In the experiment, subjects are required to establish rhythmic coordination under this view-sharing system, and we evaluate a performance for the rhythmic coordination in different composition-ratio conditions of the first-person views.
• 打撃力を用いた擬似牽引力提示装置の設計(テーマセッション「手」,手,実・仮想空間の知覚・認知,一般)

  濱口 英典, 安藤 英由樹, 飯塚 博幸, 前田 太郎  電子情報通信学会技術研究報告. HIP, ヒューマン情報処理  109-  (83)  97  -100  2009/06/08  [Not refereed][Not invited]
   

  人の非線形な知覚特性を考慮し,偏加速度を持ったオモリの運動を利用した擬似牽引力の提示デバイスが研究されている.しかし,従来手法ではクランクスライダ機構のため小型・軽量化が困難であった.そこで,本研究では小型軽量で従来と同等の偏加速度運動を実現する機構として回転する2節リンクの先端にオモリを載せ,固定された壁面に周期的に衝突させる機構を提案する.本装置では衝突時の打撃力によって短時間の大きな推力を生成し,回転時のオモリの可動によって長時間の小さな推力を生成する.本発表では,効果的な偏加速度運動を生成するために,衝突部の構造,回転時のオモリの軌道,の2点に関する設計論について述べる.
• 2A2-K01 The transmission characteristic analysis for transmit tactile information using nail-mounted tactile display : The study of active touch tactile display using vibration on fingernail (2)

  Ando Hideyuki, Yumura Takeshi, Iizuka Hiroyuki, Watanabe Junji, Maeda Taro  ロボティクス・メカトロニクス講演会講演概要集  2009-  "2A2  -K01(1)"-"2A2-K01(4)"  2009/05/25  

  In this paper, we propose a method to transmit tactile information from one person to another using nail-mounted tactile display. Our proposed method conveys tactile information which is obtained by detecting the vibration on the nail of a sender when tracing a texture, and generates a vibration on the nail of a receiver to re-create the tactile perception while the subject tracing on a flat surface. Therefore, we measured the vibration on the subject's nail when tracing different kinds of textures, and analyzed its characteristics to find essential factors in order to share tactile perceptions with two people.
• 1P1-E09 Can Human Detect the Difference between Machine and Human through Nonverbal Interaction? : Emergence of Turn-taking on behaviour-based turing test

  Iizuka Hiroyuki, Ando Hideyuki, Maeda Taro  ロボティクス・メカトロニクス講演会講演概要集  2009-  "1P1  -E09(1)"-"1P1-E09(4)"  2009/05/25  [Not refereed][Not invited]
   

  To establish a harmonic interaction between a human and a computer, we reconsider human interactions that establish natural communication. Instead of investigating verbal communication, we use the simple and low-level environment where inputs and outputs of subjects are restricted in a low dimension at the behavioral level. Our final goal is to clarify with the simple environment how humans can create human-like interaction such as an interaction that produces the feeling of human. To achieve it, behavior-based turing-test is proposed here. As a result, it is shown that the emergence of turn-taking behavior plays an important role to pass our behavior-based turing test. The results are also discussed with the attractor superimposition.
• Performance Evaluation of Recommendation Algorithms Based on Rating-recommendation Interaction

  山下 晃弘, 川村 秀憲, 飯塚 博幸, 大内 東  情報処理学会論文誌数理モデル化と応用（TOM）  2-  (2)  47  -57  2009/03/27  [Not refereed][Not invited]
   

  The problem of information overload spreading across the Internet has been causing serious inefficiency in browsing and searching for information. As a way to overcome the problem, the recommender systems are recently used in many E-commerce sites. Many algorithms have been proposed to improve the accuracy of recommendation based on user ratings. The relation between recommender systems and users is rather interactive in the sense that recommendations decides which items are recommended to users and the results of ratings by users will affect the next recommendations. However, conventional studies have not considered the interactive aspects so much. Therefore, our aim of this paper is to propose a new evaluation model using multiagent modeling where the recommender system and agents (as users) interacts with each other. The properties of typical recommendation algorithms such as user-based and itembased collaborative filtering will be analyzed with our proposed model. Our results also suggest the possibilities to propose a novel and effective recommendation algorithm.
• 擬似牽引力提示装置の装着方法が牽引力錯覚に及ぼす影響

  長江依奈, 安藤英由樹, 安藤英由樹, 米村朋子, 米村朋子, 飯塚博幸, 飯塚博幸, 前田太郎, 前田太郎  日本バーチャルリアリティ学会大会論文集(CD-ROM)  14th-  2009
• 一人称視点映像重ね合わせを用いた視覚・運動共有手法の検討

  川崎宏記, 岡本信, 中村和志, 中村和志, 米村朋子, 米村朋子, 飯塚博幸, 安藤英由樹, 前田太郎  日本バーチャルリアリティ学会大会論文集(CD-ROM)  14th-  2009
• ロボット操縦における「つもり」の伝送と検出の検討

  岡田慎矢, 坂口翔太, 丹羽真隆, 飯塚博幸, 安藤英由樹, 前田太郎, 飯塚博幸, 安藤英由樹, 前田太郎  日本バーチャルリアリティ学会大会論文集(CD-ROM)  14th-  2009
• 場所と興味を反映した情報提示のための頭部搭載スクリーンを用いた遭遇型ディスプレイの提案

  廣瀬光彦, 近藤大祐, 飯塚博幸, 安藤英由樹, 前田太郎  日本バーチャルリアリティ学会大会論文集(CD-ROM)  14th-  2009
• 実空間とVR空間の視点を一致させたビデオシースルーHMDの開発と評価

  黒崎敬太郎, 濱田和孝, 近藤大祐, 飯塚博幸, 安藤英由樹, 前田太郎  日本バーチャルリアリティ学会大会論文集(CD-ROM)  14th-  2009
• 前庭電気刺激における頭部電流経路モデルの改善

  宮田祐樹, 濱田和孝, 飯塚博幸, 安藤英由樹, 前田太郎  日本バーチャルリアリティ学会大会論文集(CD-ROM)  14th-  2009
• Bio-Inspired Ambient Interfaces : Human Behavior Supporting Based on Attractor Superimposition Theory

  MAEDA Taro, ANDO Hideyuki, IIZUKA Hiroyuki  IPSJ SIG Notes. CVIM  2008-  (115)  81  -90  2008/11/20  [Not refereed][Not invited]
   

  The present Global COE Program "Founding Ambient Information Society Infrastructure" by Osaka University's Graduate School of Information Science and Technology aims at establishing ambient interface technologies that can harmonize human-environment interactions to naturally lead to a more suitable state with the integration of information science and biologically-inspired. As a possible way to achieve such a technology, we propose the concept of Parasitic Humanoid that is a system consisting of wearable interface devices that enable rather intuitive interactions with wearers than conventional interaction ways such as key-typing, device-control, and graphical user interfaces. We also introduce a novel way for human behavioural supports with the Parasitic Humanoid on the basis of the concept of attractor superimposition caused by mutual human-environment couplings.
• Bio-Inspired Ambient Interfaces : Human Behavior Supporting Based on Attractor Superimposition Theory

  MAEDA Taro, ANDO Hideyuki, IIZUKA Hiroyuki  Technical report of IEICE. PRMU  108-  (327)  81  -90  2008/11/20  [Not refereed][Not invited]
   

  The present Global COE Program "Founding Ambient Information Society Infrastructure" by Osaka University's Graduate School of Information Science and Technology aims at establishing ambient interface technologies that can harmonize human-environment interactions to naturally lead to a more suitable state with the integration of information science and biologically-inspired. As a possible way to achieve such a technology, we propose the concept of Parasitic Humanoid that is a system consisting of wearable interface devices that enable rather intuitive interactions with wearers than conventional interaction ways such as key-typing, device-control, and graphical user interfaces. We also introduce a novel way for human behavioural supports with the Parasitic Humanoid on the basis of the concept of attractor superimposition caused by mutual human-environment couplings.
• Bio-Inspired Ambient Interfaces : Human Behavior Supporting Based on Attractor Superimposition Theory

  MAEDA Taro, ANDO Hideyuki, IIZUKA Hiroyuki  Technical report of IEICE. Multimedia and virtual environment  108-  (328)  81  -90  2008/11/20  [Not refereed][Not invited]
   

  The present Global COE Program "Founding Ambient Information Society Infrastructure" by Osaka University's Graduate School of Information Science and Technology aims at establishing ambient interface technologies that can harmonize human-environment interactions to naturally lead to a more suitable state with the integration of information science and biologically-inspired. As a possible way to achieve such a technology, we propose the concept of Parasitic Humanoid that is a system consisting of wearable interface devices that enable rather intuitive interactions with wearers than conventional interaction ways such as key-typing, device-control, and graphical user interfaces. We also introduce a novel way for human behavioural supports with the Parasitic Humanoid on the basis of the concept of attractor superimposition caused by mutual human-environment couplings.
• Extending homeostatic neural controller for adaptive behaviour

  IIZUKA Hiroyuki  IPSJ SIG Notes. ICS  2008-  (20)  55  -60  2008/03/06  

  A homeostatic neural controller is extended by exploiting the internal dynamics of a neural network in the absence of sensory input and also by avoiding the loss of internal variability that is caused by a local plastic mechanism. The extended method can solve a contingent link between internal and behavoiural stability where homeostasis remain unaffected even under disruptions of behaviours. The method allows the generation of reliable adaptation to morphological disruptions in a simple simulated vehicle using a homeostatic neurocontroller that has been selected to behave homeostatically while performing the desired behaviour but non-homeostatically in other circumstances. The performance of the extended method is compared with simple homeostatic neural controllers. As a result, it is shown that the extended homeostatic networks are more adaptive and can adapt to the environmental changes that happen more than once.
• Performance Evaluation of User-based and Item-based Collaborative Filtering by Multi-agent Modeling

  YAMASHITA AKIHIRO, KAWAMURA HIDENORI, IIZUKA HIROYUKI, OHUCHI AZUMA  IPSJ SIG Notes  68-  (17)  141  -144  2008/03/04  [Not refereed][Not invited]
   

  Information overload problem has expanded further more. A recommender system provides personalized recommendation for each user to reduce the problem. Many techniques to maximize the accuracy of recommendation based on browse history or purchase of certain products have been already proposed. Moreover, the recommendation result influences the user's behavior. Basically, the recommender system and the users are interactive, however, this dynamics had not been researched. In this research, we modeled the user as a purchase-rating agent, and analyzed the performance of the recommendation algorithm considering the system-user interaction. In this paper, we report a result of the analysis of user-based and and item-based collaborative filtering.
• Extending homeostatic neural controller for adaptive behaviour

  IIZUKA Hiroyuki  IEICE technical report  107-  (523)  55  -60  2008/02/27  

  A homeostatic neural controller is extended by exploiting the internal dynamics of a neural network in the absence of sensory input and also by avoiding the loss of internal variability that is caused by a local plastic mechanism. The extended method can solve a contingent link between internal and behavoiural stability where homeostasis remain unaffected even under disruptions of behaviours. The method allows the generation of reliable adaptation to morphological disruptions in a simple simulated vehicle using a homeostatic neurocontroller that has been selected to behave homeostatically while performing the desired behaviour but non-homeostatically in other circumstances. The performance of the extended method is compared with simple homeostatic neural controllers. As a result, it is shown that the extended homeostatic networks are more adaptive and can adapt to the environmental changes that happen more than once.
• Communication and generation of motions by discretized / continuous visual images

  麻生紘己, 岡本信, 川崎宏記, 飯塚博幸, 安藤英由樹, 前田太郎  日本バーチャルリアリティ学会大会論文集(CD-ROM)  13th-  2008
• 21pTP-3 Embodied dynamics of agency detection in social interaction

  Iizuka Hiroyuki  Meeting abstracts of the Physical Society of Japan  62-  (2)  266  -266  2007/08/21
• 24pXK-4 Simulating Turn-Taking Dynamics

  Iizuka Hiroyuki, Ikegami Takashi  Meeting abstracts of the Physical Society of Japan  57-  (1)  240  -240  2002/03/01
• Learning of Virtual Words Utilized in Negotiation Process between Agents

  IIZUKA Hiroyuki, SUZUKI Keiji, YAMAMOTO Masahito, OHUCHI Azuma  IEICE transactions on fundamentals of electronics, communications and computer sciences  83-  (6)  1075  -1082  2000/06/25  

  Agent-based simulations are expected to enable analysis of complex social phenomena. In such simulations, one of the important behaviors of the agents is negotiation. Through-out the negotiations, the agents can make complex interactions with each other. Therefore, the ability of agents to perform negotiation is important in simulations of artificial societies. In this paper, we focus on price negotiations, in which the two sides have opposing interests. In the conventional price negotiation model, the process consists of an alternate succession of directly presented offers and counter-offers exchanging the desired prices. As an extended price negotiation model, we introduce virtual words to mimic the negotiation techniques of humans for indirectly presenting the desired price. The process of the proposed negotiation model consists of an alternate succession of offers of desired price and counter-offers of a word. The words represent the degree of the agent's demand. We propose agents with reinforcement learning who can acquire the ability to distinguish words and use them to negotiate. As a result, we will show that the virtual words became meaningful in the process of negotiations between agents whose negotiating strategies are acquired by reinforcement leaning.

Presentations

• Complexity Growth by Cooperative Interaction in Adversarial Learning  [Not invited]

  Taiki Sasaki, Wataru Noguchi, Hiroyuki Iizuka, Masahito Yamamoto

  Twenty-sixth international symposium on Artificial life and Robotics  2021/01
• Multi-agent formation by learning communication signals using DIAL in a distributed multi-agent environment  [Not invited]

  Hironobu Horiuchi, Wataru Noguchi, Iizuka Hiroyuki, Masahito Yamamoto

  Twenty-sixth international symposium on Artificial life and Robotics  2021/01
• 周辺地域の予測レーダ雨量を用いた深層学習による水路の水位予測  [Not invited]

  石川拓実, 阿曽克司, 羽黒厚志, 野口渉, 飯塚博幸, 山本雅人

  第21回計測自動制御学会システムインテグレーション部門講演会  2020/12
• カメラ映像を用いたYOLOとI3Dによる飼育動物の行動分類  [Not invited]

  加藤圭吾, 野口渉, 飯塚博幸, 山本雅人

  第21回計測自動制御学会システムインテグレーション部門講演会  2020/12
• Semi-supervised Learning Combining 2DCNNs and Video Compression for Action Recognition  [Not invited]

  Hayato Terao, Wataru Noguchi, Hiroyuki Iizuka, Masahito Yamamoto

  2020 International Conference on Vision, Image and Signal Processing(ICVISP 2020)  2020/12
• DIALを用いた通信シグナルの学習によるマルチエージェントフォーメーション  [Not invited]

  堀内宏信, 野口渉, 飯塚博幸, 山本雅人

  19回情報科学技術フォーラム(FIT2020)講演論文集, 第2分冊  2020/09
• 複数の代表点を用いたSDMMに基づく半教師あり行動認識手法  [Not invited]

  寺尾 颯人, 野口 渉, 飯塚 博幸, 山本 雅人

  19回情報科学技術フォーラム(FIT2020)  2020/09
• Learning of Evaluation Function in Digital Curling Considering the Probability of Scores at Each End  [Not invited]

  Kotaro Ataka, Wataru Noguchi, Iizuka Hiroyuki, Masahito Yamamoto

  AAAI20 Workshop, Artificial Intelligence in Team Sports  2020/02
• MixMatch based semi-supervised learning for video action recognition using 3D convolutional neural networks  [Not invited]

  Hayato Terao, Wataru Noguchi, Hiroyuki Iizuka, Masahito Yamamoto

  Twenty-fifth international symposium on Artificial life and Robotics  2020/01
• Efffect of Reactivity Artificial Medaka on Real Medaka  [Not invited]

  Katsuki Auchi, Wataru Noguchi, Hiroyuki Iizuka, Masahito Yamamoto

  twenty-fifth international symposium on Artificial life and Robotics  2020/01
• Reinforcement Learning Method with Internal World Model Training  [Not invited]

  Kenji Hirata, Hiroyuki Iizuka, Masahito Yamamoto

  2020 IEEE/SICE International Symposium on System Integration  2020/01
• Analysis of Time Series Trained by Adversarial Imitation Learning in Discrete State Neural Network Model  [Not invited]

  Seiya Yamazaki, Hiroyuki Iizuka, Masahito Yamamoto

  2020 IEEE/SICE International Symposium on System Integration  2020/01
• Analysis of Time Series Generated By Long Short-Term Memory Trained with Adversarial Imitation Learning[Seiya Yamazaki,Hiroyuki Iizuka,Masahito Yamamoto]  [Not invited]

  Seiya Yamazaki, Hiroyuki Iizuka, Masahito Yamamoto

  2019 IEEE Symposium Series on Computational Intelligence (IEEE SSCI 2019)  2019/12
• 分割した集団の学習による役割分担の獲得  [Not invited]

  荒木関 渉, 野口 渉, 飯塚 博幸, 山本 雅人

  情報処理北海道シンポジウム2019  2019/10
• Hybrid Synthetic Approach to Animal Interaction  [Not invited]

  Hiroyuki Iizuka, Yosuke Nakamoto, Masahito Yamamoto

  The 2019 Conference on Artificial Life  2019/07
• Spatial Representation of Self and Other by Superposition Neural Network Model  [Not invited]

  Wataru Noguchi, Hiroyuki Iizuka, Shigeru Taguchi, Masahito Yamamoto

  The 2019 Conference on Artificial Life  2019/07
• 3次元畳み込みニューラルネットワークを用いた店舗における顧客行動の分類  [Not invited]

  貝塚 裕, 飯塚 博幸, 山本 雅人

  ロボティクス・メカトロニクス講演会2019 （ROBOMECH2019）  2019/06

Research Projects

• Synthetic approach to perceptual illusions using cognitive deep learning model with predictive learning

  Japan Society for the Promotion of Science：Grants-in-Aid for Scientific Research

  Date (from‐to) : 2022/04 -2026/03 

  Author : 飯塚 博幸, 山本 雅人, 鈴木 啓介, 野口 渉
• リアルタイム動物行動解析に向けた圧縮動画による半教師あり学習手法の開発

  日本学術振興会：科学研究費助成事業

  Date (from‐to) : 2022/04 -2025/03 

  Author : 山本 雅人, 飯塚 博幸, 田村 康将, 野口 渉
• Increasing complexity of signals through adversarial imitation learning in cumulative cultural evolution

  Japan Society for the Promotion of Science：Grants-in-Aid for Scientific Research

  Date (from‐to) : 2020/04 -2022/03 

  Author : 飯塚 博幸

   

  本研究では，認知実験とコンピュータによる構成論的アプローチによって，単純なシグナルのやりとりでの「真似したいが真似されたくない」という敵対的模倣関係のなかから，そのシグナル上にいかにして言語的な階層構造が意図共有を通して創発可能かを明らかにすることである．初年度においては，Kirbyらの行った累積的文化進化の実験室実験を拡張することで実験する予定であったが，対面での実験が難しかったため，実験装置の作成と小規模な予備実験に留めた．実験ではサイモンゲームを用いて，味方プレイヤには真似されるように，敵プレイヤには真似されないように色パターンを生成する．予備実験結果においては，相手には真似されないように色パターン系列を生成すると，生成されるパターンの複雑化がシミュレーションと同様に見られることを明らかにした．生成されたパターン系列は，複雑さの指標として圧縮率と構造化の指標としてSQUITURアルゴリズムを用いて評価した．しかし，生成されるパターンにおいて，構造化されるようなものは得られなかった．一方で，シミュレーションでは，機械学習で注目を集めている敵対的生成ネットワークを利用して，敵対的模倣学習のモデル化を行った．敵対的生成ネットワークでは，実画像を利用することで，実画像と同程度の複雑さをもち，かつ，リアリティを人に感じさせる構造的特徴を学習可能である．これを利用して敵対的模倣学習をモデル化することで，前回の公募課題のときには見られなかった2者間において，時系列パターンの複雑が生じることを示した．
• Emergence of Grammar in Imitation Learning using Deep Learning

  Japan Society for the Promotion of Science：Grants-in-Aid for Scientific Research Grant-in-Aid for Scientific Research on Innovative Areas (Research in a proposed research area)

  Date (from‐to) : 2018/04 -2020/03 

  Author : 飯塚 博幸

   

  初年度において関数の表現が豊かなフィードフォワードニューラルネットワークを用いても，相手を真似したいが，相手からは真似されたくない状況である敵対的模倣学習によって時系列が複雑化することが明らかになった．最終年度は，まず，敵対的模倣が複雑化に寄与しているのかを確かめるために，異なる真似関係構造がもたらす時系列の複雑さを明らかにした．相互作用の種類として，２体のそれぞれのエージェントに，模倣のみ（真似したい），被模倣のみ（真似されたくない），敵対的模倣の３種類を用いてシミュレーションを行った．結果として，少なくとも一方が敵対的模倣のときのみ時系列は複雑化し，そのときに相手が被模倣もしくは敵対的である必要があることが明らかとなった．両者の真似されたくないというのが複雑化の必要条件であり，かつ，少なくともどちらか一方が真似したいという敵対的模倣が必要であるとわかった． さらに，敵対的模倣学習がもたらす時系列の時間方向の複雑化を示すために，記憶を保持できるリカレントニューラルネットワークの一つであるLSTMを用いてモデルの構築とシミュレーションを行った．結果，初年度のモデルと同様に，リアプノフ指数が正となり，時系列が複雑化することがわかった．そこで，記憶のないモデル時に見られなかったような時間方向への構造化を定量的に示すために，ZIP圧縮を用いて生成時系列を圧縮させた．時系列がカオスになっているエポックのうち，その中でも相対的に圧縮できるパターンが生まれていることが明らかとなった．このときの時系列の遷移パターンを可視化するために，N-gramモデルを用いて時系列を有限状態文法で表し，ノード数・パス数ともに小さくなっていることを示し，より単純なグラフになっていることがわかった．記憶を持つ場合には，空間方向だけでなく時間方向も扱えるため，時間方向の複雑化・構造化が生じた．
• Establishing mutual communication between organism and machine using deep learning

  Japan Society for the Promotion of Science：Grants-in-Aid for Scientific Research Grant-in-Aid for Scientific Research (C)

  Date (from‐to) : 2017/04 -2020/03 

  Author : Iizuka Hiroyuki

   

  We constructed a mutual interaction system between machine and fish (medaka). The system can generate and show visual stimuli of machine movements in response to the movements of the real medaka which are detected in real time. Using this experimental apparatus, we compared the real medaka behaviors to the artificial movements generated by reactive (mutual) or non-reactive (unidirectional) way. Real medaka were more interested in reactive artificial movements and spent more time on the screen showing the reactive artificial movements than non-reactive one. In other words, it was possible to induce specific behaviors in real medaka under the mutual interaction. It can be said that the communication-like interaction between the artifact and the medaka has been realized.
• Development of Robot Control Interface based Mutual Learning of Users and Machines.

  Japan Society for the Promotion of Science：Grants-in-Aid for Scientific Research Grant-in-Aid for Scientific Research (C)

  Date (from‐to) : 2015/04 -2018/03 

  Author : Yamamoto Masahito

   

  In this research, we have proposed a mutual learning interface between human and machine where the machine exploits the prediction errors to read user’s intention. To do this, we extracted human intention from body movements, especially hand movements, and associate with movements of multi-degree of freedom spider robot, thereby constructing interface to operate robot only from hand movements. Since the hand movements reacts the intention that varies depending on the individual user, the correspondence between the hand movements and the operation of the controlled object is built using machine learning. It is shown that the proposed interface can adapt to multiple behaviors of the robot.
• 正直シグナルの伝播による人らしさを生み出す操縦インタフェースの構築

  日本学術振興会：科学研究費助成事業 新学術領域研究(研究領域提案型)

  Date (from‐to) : 2015/04 -2017/03 

  Author : 飯塚 博幸

   

  前年度においてPerceptual Crossing実験を行うことで，人の非言語相互作用に時間遅れをいれた場合，400msから500msの時間遅れが入ってしまうと例え人が操作していたとしても人らしさが大きく失われることがわかった．これは，ロボットが人と相互作用を行っている状況に当てはめると，相手の動作に対する人の応答タイミングから，400ms以上ロボットの動作が遅れてしまうとロボットの動きは人らしくなり得ないということを意味している．これを改善するために本年度において，引き続き人同士の相互作用の解析を行い，人がロボットを操縦する際，ロボットが人らしく振る舞うための方法論の構築を行った．まず，時間遅れに対して人は振る舞いを変えることで相互作用の頑健性を上げていることがわかった．そこでは，両者が相互作用を行うときに生じる接触を意味する振動刺激の間隔が遅くなっていることがわかった．これは両者の相互作用のリズムを遅くすることで，時間遅れが相互作用に入ったときにお互いの応答タイミングに幅が生じたためだと考えられる．次に，この人の適応行動を利用することで，ロボットの応答タイミングが遅れても人らしく振る舞うことのできる方法を提案した．アイデアとしては，外部からインタフェースとして相互作用のリズムを遅くしてやることで，相互作用の頑健性を向上できるではないかと考えた．方法としては，Perceptual Crossing実験内での運動ゲインを下げ，運動の効果を落とした．これは必ずしも相互作用のリズムを遅くすることにはつながらないが，結果的に相互作用のリズムを落とすことに成功した．これにより，相互作用の頑健性の向上も観察された．また，定量的に移動エントロピーを用いることで，時間遅れがあっても相互作用が改善されていることを示した．
• EEG Communication between Two using Neurofeedback Training

  Japan Society for the Promotion of Science：Grants-in-Aid for Scientific Research Grant-in-Aid for Challenging Exploratory Research

  Date (from‐to) : 2013/04 -2015/03 

  Author : IIZUKA Hiroyuki

   

  Neurofeedback Training (NFT) is a training to regulate brain activities with visual or sound feedback of their own brain activities to subjects. This study extends the conventional NFT to bilateral NFT between two where the brain waves are communicated directly and used as the feedback. In the experiments, the powers of alpha waves of EEG are displayed as a visual feedback. Our results show that alpha power of subjects’ EEG can be enhanced in the bilateral NFT and that the subjects who can successfully enhance the alpha power is also able to regulate the alpha in the conventional individual NFT.
• The detection and transmission of "Tumori": The study of scalabilityof the voluntariness in tele-operation

  Japan Society for the Promotion of Science：Grants-in-Aid for Scientific Research Grant-in-Aid for Scientific Research (A)

  Date (from‐to) : 2010 -2012 

  Author : MAEDA Taro, ANDO Hideyuki, IIZUKA Hiroyuki, SUZUKI Takahumi

   

  Our research project investigated temporally-segmented behavioral intentions when performing motion planning. The segmented behavioral intention is called “Tsumori”. We developed a novel way of classifying and estimating Tsumori to control a humanoid robot with a large number of DOF with a simple interface. Our developed technology does not lose the sense of agency when controlling a robot in a real-time manner, which means that they can control a robot like moving their parts of body. To achieve this, we successfully relaxed the conditions of sense of agency on Tsumori controller. “Tsumori” was also examined in the brain activities. We successfully detected the brain and physiological responses to the “Tsumori” for the functional purpose. These findings and further development of brain models extend the application of segmented behavioral intentions “Tsumori”
• Experimental Study of Agency feeling by Sensory Integration of Vision, Tactile and Motion

  Japan Society for the Promotion of Science：Grants-in-Aid for Scientific Research Grant-in-Aid for Young Scientists (B)

  Date (from‐to) : 2010 -2011 

  Author : IIZUKA Hiroyuki

   

  The aim of this study is to clarify how the distinction of self-(sense of agency, SOA) and other-produced behavior can be synthesized and recognized in multisensory integration as our cognitive processes. To address this issue, we use tickling paradigm that it is hard for us to tickle ourselves. In our hypothesis, integration of vision, proprioception, and motor commands forms the SOA and disintegration causes the breakdown the SOA, which causes the feeling of others, producing tickling sensation even by tickling oneself. This hypothesis was tested.
• 構成論的アプローチによる能動的運動がもたらす知覚と認知の複雑さに関する研究

  日本学術振興会：科学研究費助成事業 特別研究員奨励費

  Date (from‐to) : 2005 -2007 

  Author : 飯塚 博幸

   

  本年度は,実際に認知実験に見られる主体性に関する認知実験をもとにして,相互作用における能動性と主体性のモデル化を行った.人間は他人との相互作用において,自己の意図性をそのやりとりされる運動の中に表現する.その主体性は一人の運動の表現から導かれるものではなく,相互作用そのものに埋め込まれている(例えば,Trevarthenらの実験(1985)).この間主観的な社会的相互作用における主体性の検出運動ダイナミクスのシミュレーションを行い,大域的な力学系の観点から解析を行った. シミュレーションでは,相手のエージェントがニューラルネットワークを使ってリアルタイムに応答しているのか,それとも,以前相互作用したときに録画された運動をリプレイするだけの非応答エージェントであるのか,を区別することをもって相手の主体性の判断とした. この区別ができるエージェントを進化的アルゴリズムによって獲得し,その運動と内部ダイナミクスの解析を行った.結果として,ここでのエージェントの主体性はアトラクター間のトランジェントダイナミクスが相互に絡み合うことによって実現された.また,その主体性検出のための運動ダイナミクスは,ノイズに対する大域的なダイナミクスのロバスト性と接触タイミングを揺らがすための入力に対する鋭敏性と振る舞いの多様性を利用することで十分可能であることがわかった.このことは,相手の主体性を認知するために,複雑な情報を統合する個々の認知機構は必ずしも必要条件とはならず,むしろ,相互作用の自体のリアルタイム性とノイズに対する頑健性によって実現が可能であることを意味している.これらのシミュレーション結果は,人の主体性を扱うような難解な認知の問題に対しても,モデルを複雑化して理解するのではなく,環境とエージェントを簡素に記述し,その相互作用から考えるという身体性モデリングの一つの可能性を示した.
• 交渉エージェント間における合意形成に関する研究

  日本学術振興会：科学研究費助成事業 特別研究員奨励費

  Date (from‐to) : 2001 -2003 

  Author : 飯塚 博幸

   

  協調的でもあり競争的でもある交渉という環境において、そのお互いの目的が協調的でかつ競争的であるシミュレーション環境のモデル化を行い、そのような環境における各エージェントの学習機構の開発とそのエージェントが学習によって獲得した内部構造の解析を行った。さらに、2エージェント間の合意形成の1つとして、ここでは、turn-takeの構造に着目した。Turn-takeの振る舞いは自分の目的を達成しながらも、相手の要求に応えて自分の目的を変化させるという交捗過程には必要な構造を含んでいる。通常、一人の特定の相手に対する適応的な戦略構造等に主眼がおかれるが、ここでは、未知の相手との協調行動の創発、適応可能性について注目した。 シミュレーションの結果、幾何学的な軌跡を描くgeometric turn-taking、軌跡やターンの切り替えが規則的に生じないchaotic turn-taking、ノイズの不安定性を利用するnoise-driven turn-takingの3つのカテゴリーに分けられる協調行動としての運動が得られた。これらの進化して得られたエージェントを、世代を変えて相互作用をさせ、得られている振る舞いの複雑さと2者の協調での運動の関係について調べた。geometric turn-takingを行うエージェントは限定された相手とturn-takingを構築することができる。一方、chaotic turn-takingを行うエージェントは比較するとgeometricなものより多くのものとturn-takingを行うことが可能であることがわかった。つまり、協調行動に対して、振る舞いの多様性が、従来の特定の相手に対する適応行動だけでなく、未知の相手に対する潜在的な適応行動を保持しうることをシミュレーションによって示した。こうしたadaptabilityのシミュレーションの結果は本研究が初めてである。