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Affiliation Department |
Department of Computer Science
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Title |
Professor |
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Contact information |
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External Link |
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INUZUKA Nobuhiro
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Degree
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Doctor (Engineering) ( Nagoya Institute of Technology )
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Master of Engineering ( Nagoya Institute of Technology )
Research Areas
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Informatics / Intelligent informatics
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Informatics / Database
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Informatics / Theory of informatics
From School
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Nagoya Institute of Technology Faculty of Engineering Graduated
- 1987.03
Country：Japan
From Graduate School
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Nagoya Institute of Technology Graduate School, Division of Engineering Doctor's Course Completed
- 1992.03
Country：Japan
External Career
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Research Fellow of the Japan Society for the Promotion of Science Special researcher of the Japan Society for the Promotion of Science
1990.04 - 1992.03
Country：Japan
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Japan Society for the Promotion of Science, Postdoctoral Fellow for Research Abroad Special researcher of the Japan Society for the Promotion of Science
1994.04 - 1996.03
Country：Japan
Professional Memberships
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The Japanese Association of Student Counseling
2012.01
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Philosophy of Science Society, Japan
2008.04
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Association for Computing Machinery
2005.04
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The Society if Instrument and Control Engineers
2004.04
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Information Processing Society of Japan
2003.04
Research Career
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Knowledge Discovery Algorithms for Analyzing Human Relationships
Grant-in-Aid for Scientific Research
Project Year： 2015.04 - 2019.03
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Development of Student Counseling Record Management System Forcusing Counseling Structure
The Other Research Programs
Project Year： 2011.12 - 2012.07
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Research in Information Technology to Establish Scientific and Reasonable Methodology in Student Counseling
Grant-in-Aid for Scientific Research
Project Year： 2011.05 - 2013.03
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Usability Tests of a Multi-Relational Data Mining Method
JST Comprehensive Support Programs for Creation of Regional Innovation
Project Year： 2010.10 - 2011.03
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Development of a Data Analysis System Based-on Relation Data Mining Methods
JST Comprehensive Support Programs for Creation of Regional Innovation
Project Year： 2009.10 - 2010.03
Papers
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Classification of Buzzwords by Focusing on Time Trends Using Twitter Data Reviewed International journal
Juno Hashimoto, Atsuko Mutoh, Koichi Moriyama, Azusa Yokogoshi, Eiko Yoshida, Tohgoroh Matsui, and Nobuhiro Inuzuka
Proceedings of Proceedings of 2021 IEEE 10th Global Conference on Consumer Electronics (GCCE 2021) 2021.10
Language：English Publishing type：Research paper (international conference proceedings) Publisher：IEEE
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Extraction of Behavioral Patterns by Recombining Non-Negative Multiple Matrix Factorization and Clustering Results Reviewed International journal
Shogo Yasui, Atsuko Mutoh, Koichi Moriyama, Tohgoroh Matsui, and Nobuhiro Inuzuka
Proceedings of Proceedings of 2021 IEEE 10th Global Conference on Consumer Electronics (GCCE 2021) 2021.10
Language：English Publishing type：Research paper (international conference proceedings) Publisher：IEEE
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Evaluation of Martial Arts Demonstration Focusing on Peak Timing Using Acceleration Data Reviewed International journal
Shohei Yamanaka, Kosuke Shima, Atsuko Mutoh, Koichi Moriyama, Tohgoroh Matsui, and Nobuhiro Inuzuka
Proceedings of Proceedings of 2021 IEEE 10th Global Conference on Consumer Electronics (GCCE 2021) 2021.10
Language：English Publishing type：Research paper (international conference proceedings) Publisher：IEEE
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Human motion analysis using expressions of non-separated accelerometer values as character strings Reviewed International journal
Kosuke Shima, Atsuko Mutoh, Koichi Moriyama, Nobuhiro Inuzuka
Artificial Life and Robotics 26 ( 2 ) 202 - 209 2021.05
Language：English Publishing type：Research paper (scientific journal) Publisher：Springer Japan
People generally perform various activities, such as walking and running. They perform these activities with different motions. For example, walking can be performed with or without swinging shoulders, as well as staggering and swinging arms. We assume that such differences occur based on physical and mental characteristics of humans. To analyze relations between the motions and the characteristics/conditions, it is useful to group humans according to these differences. In a previous work, we proposed a method that successfully grouped humans by analyzing accelerometer data of their bodies in a specific activity with fixed timing and duration. In this study, we tackle with a problem of grouping human in generic, variable-length activities, such as walking and running. We propose a method that detects same motions from the accelerometer data with sliding windows and merges continuous same motions into a motion. The method is robust regarding the difference in timing and duration of the motion. In our conducted experiments, the proposed method classified humans into groups appropriately, the groups which are acquired by the previous method with the same data but without assuming fixed timing and fixed duration, which are assumed in the previous method. The proposed method is robust against temporally noised data generated from the data.
Other Link： https://link.springer.com/article/10.1007/s10015-020-00668-6
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Exploration Improvement by Sequential Intrinsic Reward Generator in Deep Reinforcement Learning Reviewed
Kazuhiro Murakami, Koichi Moriyama, Tohgoroh Matsui, Atsuko Mutoh, Nobuhiro Inuzuka
14 ( 1 ) 1 - 11 2021.01
Language：Japanese Publishing type：Research paper (scientific journal) Publisher：Information Processing Society of Japan
Deep reinforcement learning is working well in the environment with high dimensional states. However, it is difficult for a reinforcement learning agent to learn an optimal policy in the environment where it hardly obtain rewards. Curiosity-driven exploration is a solution that gives intrinsic rewards to the agent in unfamiliar states to encourage it for visiting various states. This work proposes Sequential Intrinsic Reward Generator (SRG), which extends curiosity-driven exploration to a sequence of states and gives the agent intrinsic rewards for unfamiliar state transitions. Due to this sequential property, SRG is promising to work well also in partially observable Markov decision processes. The result of experiments shows that SRG worked better than other methods in such environments.
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属性情報取得範囲を考慮した友人関係生成モデル Reviewed
泉優多, 武藤敦子, 森山甲一,松井藤五郎, 犬塚信博
電気学会論文誌Ｃ電子情報システム部門誌 140 ( 12 ) 2020.12
Language：Japanese Publishing type：Research paper (scientific journal) Publisher：電気学会
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Evolution of Mate-choice Copying Adapted to Environmental Changes Reviewed International journal
Kosuke Ozeki, Atsuko Mutoh, Koichi Moriyama, Tohgoroh Matsui, and Nobuhiro Inuzuka
Proc. 2020 IEEE 9th Global Conference on Consumer Electronics (GCCE 2020) 2020.10
Language：English Publishing type：Research paper (international conference proceedings) Publisher：IEEE
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A Study on Attributes Based on Heterogeneity of Egos and Surrounding Nodes for Structural Features in Social Networks
Minoru Natsume, Hayato Ishigure, Atsuko Mutoh, Koichi Moriyama, Nobuhiro Inuzuka
37 ( 3 ) 1 - 7 2020.03
Language：Japanese Publishing type：Research paper (conference, symposium, etc.)
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A Model for Activating Community Activities by Changing Leaders Using Graph Clustering
Kosuke Hamajima, Atsuko Mutoh, Tohgoroh Matsui, Koichi Moriyama, Nobuhiro Inuzuka
37 ( 4 ) 1 - 8 2020.03
Language：Japanese Publishing type：Research paper (scientific journal)
Activate of community activities plays an important role in solving regional and national problems. In communities such as neighborhood associations, community activities sometimes carry out to enrich lives of members and improve their environment. Participation in community activities is supported by members having rights and responsibilities. However, there are few people who actually participate. That's because nonparticipants can obtain the same benefit with participants. Therefore, nomination of a leader who always participates in the activities and encourages the norm consciousness of the surrounding people is important to activate activities. In this research, we propose a community activity model introduced changes of a leader. We make community activity be activated by changing a leader.
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Analysis of Changes in Behavior Patterns of Workers Using Non-Negative Multiple Matrix Factorization Reviewed International journal
Seidai Kojima, Kosuke Shima, Atsuko Mutoh, Koichi Moriyama, and Nobuhiro Inuzuka
proc. The Twenty-Fifth International Symposium on Artificial Life and Robotics 2020 (AROB 25th 2020) 2020.01
Language：English Publishing type：Research paper (scientific journal)
Books and Other Publications
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MIT認知科学大事典
中島秀之, 他（ Role： Joint translator）
共立出版 2012.11 （ ISBN:978-4-320-09447-5 ）
Language：jpn Book type：Dictionary, encyclopedia
「認知科学」の全分野にわたって，それぞれの方法論および理論を網羅した世界に類のない事典。認知科学を構成している六つの主要分野：哲学，心理学，神経科学，計算論的知能，言語学，文化・認知・進化の中から470項目を厳選し，それぞれに対して第一級の研究者が執筆にあたっている。
登録者（犬塚）は人工知能関係の８項目程度を翻訳した。
Presentations
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エージェント間の距離がタスク達成に影響する環境下における報酬の制御
中田瑛，森山甲一，武藤敦子，松井藤五郎，犬塚信博
エージェント間の距離がタスク達成に影響する環境下における報酬の制御 SMASH21 SUMMER SYMPOSIUM
Event date： 2021.09
Language：Japanese Presentation type：Oral presentation (general)
Venue：ソフトウェア科学会
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Curiosity-Driven Search in a Multiagent Reinforcement Learning Problem
Toru Iwashina, Koichi Moriyama, Tohgoroh Matsui, Atsuko Mutoh, Nobuhiro Inuzuka
The 35th Annual Conference of the Japanese Society for Artificial Intelligence Japanese Society for Artificial Intelligence
Event date： 2021.06
Language：English Presentation type：Oral presentation (general)
Reinforcement learning has been shown to be capable of
dealing with complex control problems, e.g., automated driving. In the real world, on the other hand, people are not alone but interacting with one another. When we apply reinforcement learning to such a multiagent environment, an agent should find a way to get along with others. To do so, the agent needs to search in its strategy space efficiently. In this work, we apply the curiosity-driven search to a multiagent environment. The curiosity-driven search, which is proposed for single agent scenarios, generates intrinsic rewards that guide the agent in sparse-reward environments. The intrinsic rewards may give a good result also in a multiagent environment where the agents need to find a good combination of actions. We conducted experiments using a predator-prey problem popular in multiagent studies, and found that the learning speed in the early stage of learning was improved compared to the case without the curiosity-driven search. -
Evaluation of martial arts demonstration focusing on motion timing using acceleration data
Shohei Yamanaka, Kousuke Shima, Atsuko Mutoh, Koichi Moriyama, Tohgoroh Matsui, Nobuhiro Inuzuka
The 35th Annual Conference of the Japanese Society for Artificial Intelligence Japanese Society for Artificial Intelligence
Event date： 2021.06
Language：Japanese Presentation type：Oral presentation (general)
In martial arts such as taekwondo, it is important to know one's own skill level in order to improve. In this study, we propose a method to evaluate the performance of taekwondo, attaching a smartphone with the waist and collect acceleration data. In martial arts, including taekwondo, when a martial artist stops moving, he or she instantly holds the entire body still. The acceleration data shows a peak at the moment of this stillness. If the timing of this peak is the same in all three axes, the fighter is considered to be more skilled. In this paper, We use the difference in the timing of the three axes to calculate the feature value, and decision trees create to evaluate the movement from the acceleration data using these features as explanatory variables. We evaluated the effectiveness of decision trees and confirmed these accuracy.
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Investment Trusts Clustering Using UMAP For The Long Return International conference
Haruto Yabuuchi, Tohgoroh Matsui, Atsuko Mutoh, Koichi Moriyama, Nobuhiro Inuzuka
The 35th Annual Conference of the Japanese Society for Artificial Intelligence Japanese Society for Artificial Intelligence
Event date： 2021.06
Language：Japanese Presentation type：Oral presentation (general)
It is necessary to compare investment trusts with their investment similarity, because their actual operations
may differ from their investment policies. A method for clustering investment trusts based on their monthly return has been proposed, but it only uses 3months. In this paper, we propose a method for clustering investment trusts with long term return and using the UMAP. -
Optimization of evacuation shelter allocation avoiding intersections of evacuation routes by network division
Masaya Yamamoto, Atsuko Mutoh, Koichi Moriyama, Tohgoroh Matsui, Nobuhiro Inuzuka
The 35th Annual Conference of the Japanese Society for Artificial Intelligence Japanese Society for Artificial Intelligence
Event date： 2021.06
Language：Japanese Presentation type：Oral presentation (general)
In recent years, there have been many occurrences of earthquakes and other large-scale disasters. Since the Great East Japan Earthquake revealed that many residents do not know where to evacuate to in the event of a large-scale disaster, evacuation shelter allocation is currently an important issue. Okada et al. proposed a method for allocating evacuation centers using data on people's stay histories. However, this method has a problem that it does not take into account evacuation routes. In this study, we propose a method to determine whether or not the network in the area to be evacuated can be divided into buildings and evacuation shelters, and to obtain the allocation of evacuation shelters without intersecting evacuation routes. As a result of evaluation experiments, we found that the proposed method was able to avoid the crossing of evacuation routes, while the conventional method had the possibility of crossing evacuation routes.
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社会ネットワークの社会的属性を特徴づける構造的属性に関する研究 International conference
細木 聡, 犬塚 信博, 武藤 敦子, 森山 甲一
人工知能学会第35回全国大会 人工知能学会
Event date： 2021.06
Language：Japanese Presentation type：Oral presentation (general)
社会ネットワーク分析において、各ノードの周囲の構造的属性は有用な働きをする可能性がある。夏目らは、構造的異質性属性を与えるオペレータを定義し、これによって得られた属性を適用した形式概念分析によって、具体的なエゴの振る舞いを分析した。しかし、限られた属性とオペレータの適用方法を対象としており、構造と関連する広い範囲の属性を対象とする必要がある。そこで、本研究では構造的な異質性に基づく新たな属性を定義し、それらも含めて有用性を調査した。その結果、いくつかのオペレータと属性の組合せで有用な結果を得た。
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Estimation of performance evaluation factors by analyzing the centrality in the meeting network International conference
Yuta Mizuno, Atsuko Mutoh, Koichi Moriyama, Tohgoroh Matsui, Nobuhiro Inuzuka
The 35th Annual Conference of the Japanese Society for Artificial Intelligence Japanese Society for Artificial Intelligence
Event date： 2021.06
Language：Japanese Presentation type：Oral presentation (general)
In recent years, some researches aimed at searching for important persons on social networks using the centrality have been focused. In this study, by measuring the correlation between each centrality of the meeting network in the office and various indicators, we clarified the characteristics of each centrality, and estimated the factors for evaluating the performance in the company.
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非負値多重行列因子分解による購買および TV視聴パターンの可視化
安井彰悟, 武藤敦子, 森山甲一, 松井藤五郎, 犬塚信博
情報処理学会第83回全国大会 情報処理学会
Event date： 2021.03
Language：Japanese Presentation type：Oral presentation (general)
本研究では，小島らの非負値多重行列因子分解とクラスタリングを用いたユーザ行動パターン抽出方法における，因子分解結果からクラスタ内ユーザの行動特徴を解釈するのが複雑であるという問題に対して，因子行列と各クラスタ中心のユーザの因子寄与度を掛け合わせることによって，クラスタ内ユーザの行動特徴を可視化する手法を提案する。
その後，従来手法と同様に，クラスタ内ユーザの個人属性を決定木学習することで，行動特徴と個人属性の関係性について分析する。
最後に，ユーザの商品の購買と，TV視聴時間帯の関係性について本手法を用いて分析を行い，有効性を確認する。 -
Automatic Generation of Behavioral Rules for Pedestrian Simulations Using Reinforcement Learning
Himeka Kobayashi, Koichi Moriyama, Tohgoroh Matsui, Atsuko Mutoh, Nobuhiro Inuzuka
Event date： 2021.03
Language：Japanese Presentation type：Oral presentation (general)
In designing pedestrian simulations, it is common for model designers to prepare in advance behavioral rules of the pedestrians. To reduce the burden on the designers, we aim to automatically generate the rules using reinforcement learning. In this work, we consider counter-flow simulations where agents move toward each other. They decide their actions based on visual information. This work designs their states to avoid collisions in the simulations. From the simulation experiments, we found that the proposed agents learn appropriate behavioral rules to arrive at the destination while avoiding collisions.
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高次元連続観測空間における安全な強化学習
梅本 匠, 松井 藤五郎, 武藤 敦子, 森山 甲一, 犬塚 信博
情報論的学習理論と機械学習研究会 電子情報通信学会
Event date： 2021.03
Language：Japanese Presentation type：Oral presentation (general)
Venue：オンライン
本論文では，連続状態空間における成功確率と収益に基づく安全な強化学習の手法であるCSEQを高次元に拡張する方法を提案する．被災地や宇宙などの人が直接行くことのできない危険な環境でロボットの活躍が期待されている．強化学習は試行錯誤に基づいてより良い行動を学習する機械学習の手法であり，強化学習手法の中でも危険回避行動を学習することに着目した安全な強化学習として成功確率と収益に基づくEQという手法が提案されている．これを連続状態空間に拡張した手法がCSEQであり，2次元空間上のシンプルな問題ではその有効性が確認されている．しかしながら，安全な強化学習を活用したいロボットの問題などの観測値は高次元で与えられることがほとんどである．そこで我々はVAEでモデル化された潜在変数の平均値を用いて高次元連続空間を扱うことのできる安全な強化学習を提案する．また，高次元連続状態空間の例題を用いてその有効性を検証した．
Industrial Property Rights
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Record Management System Conseling based-on Counseling Structure
Nobuhiro Inzuuka, Atsuko Mutoh, Naotaka Oda
Application no：特願2011-999999 Date applied：2011.02
Country of applicant：Domestic Country of acquisition：Domestic
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Friendship Prediction System
Nobuhiro Inuzuka, Tomofumi Nakano, Kosaku Shimomura, Hiroshi Matsuo
Application no：特願2008-34078 Date applied：2008.02
Announcement no：特開2009-193396 Date announced：2009.08
Patent/Registration no：5283059 Date registered：2013.06 Date issued：2013.06
Country of applicant：Domestic Country of acquisition：Domestic
Awards
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2019年度人工知能学会全国大会優秀賞
2019.06 人工知能学会 非負値多重行列因子分解の因子行列を用いたクラスタリングと決定木学習によるオフィスの入退室データの分析
小島 世大, 石槫 隼人, 坂田 美和, 武藤 敦子, 森山 甲一, 犬塚 信博
Award type：Award from Japanese society, conference, symposium, etc. Country：Japan
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情報処理学会全国大会学生奨励賞
2013.03 情報処理学会
西山瑞紀
Award type：Award from Japanese society, conference, symposium, etc. Country：Japan
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第９回情報学ワークショップ奨励賞
2011.11 第９回情報学ワークショップ実行委員会
小田尚宜, 武藤敦子, 犬塚信博
Award type：Award from Japanese society, conference, symposium, etc. Country：Japan
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第８回情報学ワークショップ奨励賞
2010.12 情報学ワークショップ実行委員会
松島裕, 犬塚信博
Award type：Award from Japanese society, conference, symposium, etc. Country：Japan
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第８回情報学ワークショップ優秀論文賞
2010.12 情報学ワークショップ実行委員会
中野裕介, 犬塚信博
Award type：Award from Japanese society, conference, symposium, etc. Country：Japan
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第７回情報学ワークショップ奨励賞
2009.11 情報学ワークショップ実行委員会
牧野敏行,犬塚信博
Award type：Award from Japanese society, conference, symposium, etc. Country：Japan
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電気関係学会東海支部連合大会奨励賞
1996.04 -
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Country：Japan
Scientific Research Funds Acquisition Results
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人間関係分析のための知識発見アルゴリズム
2015.04 - 2019.03
科学研究費補助金 基盤研究(C)
犬塚信博
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科学的・合理的な学生相談手法を確立するための情報科学的研究
2011.04 - 2013.03
科学研究費補助金 挑戦的萌芽研究
犬塚信博、粥川 裕平, 武藤 敦子