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Created page with "'''Home * People * Naoyuki Kubota''' FILE:NaoyukiKubota.jpg|border|right|thumb| Chia-Hsiu Kao <ref>[https://www.researchgate.net/profile/Naoyuki_Kubota Na..."
'''[[Main Page|Home]] * [[People]] * Naoyuki Kubota'''
[[FILE:NaoyukiKubota.jpg|border|right|thumb| Chia-Hsiu Kao <ref>[https://www.researchgate.net/profile/Naoyuki_Kubota Naoyuki Kubota | Tokyo Metropolitan University, Tokyo | TMU | Faculty and Graduate School of System Design]</ref>]]
'''Naoyuki Kubota''',<br/>
a Japanese engineer, researcher in the field of [https://en.wikipedia.org/wiki/Robotics robotics] and [https://en.wikipedia.org/wiki/Computational_intelligence computational intelligence], and professor at the [https://en.wikipedia.org/wiki/Tokyo_Metropolitan_University Tokyo Metropolitan University] and head of the Kubota laboratory <ref>[http://www.comp.sd.tmu.ac.jp/kubota-lab/hp/member/member_en.htm Tokyo Metropolitan University KUBOTA laboratory]</ref>.
He received a Ph.D. in engineering from [https://en.wikipedia.org/wiki/Nagoya_University Nagoya University] in 1997.
His recent research includes human and smart machine co-learning with the [https://en.wikipedia.org/wiki/Brain%E2%80%93computer_interface Brain-computer interface], also applied to [[Go]] playing.
=Co-Learning with BCI=
Abtract from ''Human and Smart Machine Co-Learning with [https://en.wikipedia.org/wiki/Brain%E2%80%93computer_interface Brain Computer Interface]'' <ref>[[Chang-Shing Lee]], [[Mei-Hui Wang]], [[Li-Wei Ko]], [[Naoyuki Kubota]], [[Lu-An Lin]], [[Shinya Kitaoka]], [[Yu-Te Wang]], [[Shun-Feng Su]] ('''2018'''). ''[https://www.semanticscholar.org/paper/Human-and-Smart-Machine-Co-Learning-with-Brain-Lee-Wang/0a06064108f2ad7319bc3ff0b37ccc6036d82f78 Human and Smart Machine Co-Learning with Brain Computer Interface]''. [https://arxiv.org/abs/1802.06521 arXiv:1802.06521]</ref>
[[Learning|Machine learning]] has become a very popular approach for [https://en.wikipedia.org/wiki/Cybernetics cybernetics] systems, and it has always been considered important research in the [https://en.wikipedia.org/wiki/Computational_intelligence Computational Intelligence area]. Nevertheless, when it comes to smart machines, it is not just about the methodologies. We need to consider systems and cybernetics as well as include human in the loop. The purpose of this article is as follows: (1) To integrate the open source Facebook AI Research (FAIR) [https://en.wikipedia.org/wiki/Darkforest Darkforest] program of [https://en.wikipedia.org/wiki/Facebook Facebook] with [https://en.wikipedia.org/wiki/Item_response_theory Item Response Theory] (IRT), to the new open learning system, namely, [[DDF]] learning system; (2) To integrate DDF Go with Robot namely Robotic DDF Go system; (3) To invite the professional [[Go]] players to attend the activity to play Go games on site with a smart machine. The research team will apply this technology to education, such as, playing games to enhance the children concentration on learning mathematics, languages, and other topics. With the detected [https://en.wikipedia.org/wiki/Neural_oscillation brainwaves], the robot will be able to speak some words that are very much to the point for the students and to assist the teachers in classroom in the future.
=Photo=
[[FILE:PlayingGowithDDF.jpg|none|border|text-bottom]]
[[Li-Wei Ko]], [[Chang-Shing Lee]], [[Shun-Feng Su]], [[Naoyuki Kubota]], and [[Takenori Obo]] (back row)<br/>
[[Lu-An Lin]] playing [[Go]] with [[DDF]], and the robot Palro reported real-time suggested next move to Lin
=PFML-based BCI Agent =
Abtract from ''PFML-based Semantic BCI Agent for Game of Go Learning and Prediction'' <ref>[[Chang-Shing Lee]], [[Mei-Hui Wang]], [[Li-Wei Ko]], [[Bo-Yu Tsai]], [[Yi-Lin Tsai]], [[Sheng-Chi Yang]], [[Lu-An Lin]], [[Yi-Hsiu Lee]], [[Hirofumi Ohashi]], [[Naoyuki Kubota]], [[Nan Shuo]] ('''2019'''). ''PFML-based Semantic BCI Agent for Game of Go Learning and Prediction''. [https://arxiv.org/abs/1901.02999 arXiv:1901.02999]</ref>:
This paper presents a semantic [https://en.wikipedia.org/wiki/Brain%E2%80%93computer_interface brain computer interface] (BCI) agent with [https://en.wikipedia.org/wiki/Particle_swarm_optimization particle swarm optimization] (PSO) based on a [https://en.wikipedia.org/wiki/Fuzzy_markup_language Fuzzy Markup Language] (FML) for [[Go]] [[Learning|learning]] and prediction applications. Additionally, we also establish an Open Go [https://en.wikipedia.org/wiki/Darkforest Darkforest] (OGD) cloud platform with Facebook AI research (FAIR) open source Darkforest and ELF OpenGo AI bots <ref>[https://ai.facebook.com/blog/open-sourcing-new-elf-opengo-bot-and-go-research/ Open-sourcing a new ELF OpenGo bot and related Go research], February 13, 2019</ref>. The Japanese robot Palro will simultaneously predict the move advantage in the board game Go to the Go players for reference or learning. The proposed semantic BCI agent operates efficiently by the human-based BCI data from their [https://en.wikipedia.org/wiki/Neural_oscillation brain waves] and machine-based game data from the prediction of the OGD cloud platform for optimizing the parameters between humans and machines. Experimental results show that the proposed human and smart machine co-learning mechanism performs favorably. We hope to provide students with a better online learning environment, combining different kinds of handheld devices, robots, or computer equipment, to achieve a desired and intellectual learning goal in the future.
=Selected Publications=
<ref>[https://dblp.uni-trier.de/pers/hd/k/Kubota:Naoyuki dblp: Naoyuki Kubota]</ref> <ref>[https://scholar.google.co.jp/citations?user=91umd98AAAAJ&hl=en Naoyuki Kubota - Google Scholar Citations]</ref>
* [[Chang-Shing Lee]], [[Mei-Hui Wang]], [[Chia-Hsiu Kao]], [[Sheng-Chi Yang]], [[Yusuke Nojima]], [[Ryosuke Saga]], [[Nan Shuo]], [[Naoyuki Kubota]] ('''2017'''). ''FML-based Prediction Agent and Its Application to Game of Go''. [https://arxiv.org/abs/1704.04719 arXiv:1704.04719]
* [[Chang-Shing Lee]], [[Mei-Hui Wang]], [[Sheng-Chi Yang]], [[Pi-Hsia Hung]], [[Su-Wei Lin]], [[Nan Shuo]], [[Naoyuki Kubota]], [[Chun-Hsun Chou]], [[Ping-Chiang Chou]], [[Chia-Hsiu Kao]] ('''2017'''). ''FML-based Dynamic Assessment Agent for Human-Machine Cooperative System on Game of Go''. [https://arxiv.org/abs/1707.04828 arXiv:1707.04828]
* [[Chang-Shing Lee]], [[Mei-Hui Wang]], [[Li-Wei Ko]], [[Naoyuki Kubota]], [[Lu-An Lin]], [[Shinya Kitaoka]], [[Yu-Te Wang]], [[Shun-Feng Su]] ('''2018'''). ''[https://www.semanticscholar.org/paper/Human-and-Smart-Machine-Co-Learning-with-Brain-Lee-Wang/0a06064108f2ad7319bc3ff0b37ccc6036d82f78 Human and Smart Machine Co-Learning with Brain Computer Interface]''. [https://arxiv.org/abs/1802.06521 arXiv:1802.06521]
* [[Chang-Shing Lee]], [[Mei-Hui Wang]], [[Li-Wei Ko]], [[Bo-Yu Tsai]], [[Yi-Lin Tsai]], [[Sheng-Chi Yang]], [[Lu-An Lin]], [[Yi-Hsiu Lee]], [[Hirofumi Ohashi]], [[Naoyuki Kubota]], [[Nan Shuo]] ('''2019'''). ''PFML-based Semantic BCI Agent for Game of Go Learning and Prediction''. [https://arxiv.org/abs/1901.02999 arXiv:1901.02999]
* [[Chang-Shing Lee]], [[Mei-Hui Wang]], [[Li-Chuang Chen]], [[Yusuke Nojima]], [[Tzong-Xiang Huang]], [[Jinseok Woo]], [[Naoyuki Kubota]], [[Eri Sato-Shimokawara]], [[Toru Yamaguchi]] ('''2019'''). ''A GFML-based Robot Agent for Human and Machine Cooperative Learning on Game of Go''. [https://arxiv.org/abs/1901.07191 arXiv:1901.07191]
=External Links=
* [https://researchmap.jp/read0124301/?lang=english KUBOTA Naoyuki - Researcher - researchmap]
* [http://www.comp.sd.tmu.ac.jp/kubota-lab/hp/member/member_en.htm Tokyo Metropolitan University KUBOTA laboratory]
* [https://scholar.google.co.jp/citations?user=91umd98AAAAJ&hl=en Naoyuki Kubota - Google Scholar Citations]
=References=
<references />
'''[[People|Up one level]]'''
[[Category:Researcher|Kubota]]
[[FILE:NaoyukiKubota.jpg|border|right|thumb| Chia-Hsiu Kao <ref>[https://www.researchgate.net/profile/Naoyuki_Kubota Naoyuki Kubota | Tokyo Metropolitan University, Tokyo | TMU | Faculty and Graduate School of System Design]</ref>]]
'''Naoyuki Kubota''',<br/>
a Japanese engineer, researcher in the field of [https://en.wikipedia.org/wiki/Robotics robotics] and [https://en.wikipedia.org/wiki/Computational_intelligence computational intelligence], and professor at the [https://en.wikipedia.org/wiki/Tokyo_Metropolitan_University Tokyo Metropolitan University] and head of the Kubota laboratory <ref>[http://www.comp.sd.tmu.ac.jp/kubota-lab/hp/member/member_en.htm Tokyo Metropolitan University KUBOTA laboratory]</ref>.
He received a Ph.D. in engineering from [https://en.wikipedia.org/wiki/Nagoya_University Nagoya University] in 1997.
His recent research includes human and smart machine co-learning with the [https://en.wikipedia.org/wiki/Brain%E2%80%93computer_interface Brain-computer interface], also applied to [[Go]] playing.
=Co-Learning with BCI=
Abtract from ''Human and Smart Machine Co-Learning with [https://en.wikipedia.org/wiki/Brain%E2%80%93computer_interface Brain Computer Interface]'' <ref>[[Chang-Shing Lee]], [[Mei-Hui Wang]], [[Li-Wei Ko]], [[Naoyuki Kubota]], [[Lu-An Lin]], [[Shinya Kitaoka]], [[Yu-Te Wang]], [[Shun-Feng Su]] ('''2018'''). ''[https://www.semanticscholar.org/paper/Human-and-Smart-Machine-Co-Learning-with-Brain-Lee-Wang/0a06064108f2ad7319bc3ff0b37ccc6036d82f78 Human and Smart Machine Co-Learning with Brain Computer Interface]''. [https://arxiv.org/abs/1802.06521 arXiv:1802.06521]</ref>
[[Learning|Machine learning]] has become a very popular approach for [https://en.wikipedia.org/wiki/Cybernetics cybernetics] systems, and it has always been considered important research in the [https://en.wikipedia.org/wiki/Computational_intelligence Computational Intelligence area]. Nevertheless, when it comes to smart machines, it is not just about the methodologies. We need to consider systems and cybernetics as well as include human in the loop. The purpose of this article is as follows: (1) To integrate the open source Facebook AI Research (FAIR) [https://en.wikipedia.org/wiki/Darkforest Darkforest] program of [https://en.wikipedia.org/wiki/Facebook Facebook] with [https://en.wikipedia.org/wiki/Item_response_theory Item Response Theory] (IRT), to the new open learning system, namely, [[DDF]] learning system; (2) To integrate DDF Go with Robot namely Robotic DDF Go system; (3) To invite the professional [[Go]] players to attend the activity to play Go games on site with a smart machine. The research team will apply this technology to education, such as, playing games to enhance the children concentration on learning mathematics, languages, and other topics. With the detected [https://en.wikipedia.org/wiki/Neural_oscillation brainwaves], the robot will be able to speak some words that are very much to the point for the students and to assist the teachers in classroom in the future.
=Photo=
[[FILE:PlayingGowithDDF.jpg|none|border|text-bottom]]
[[Li-Wei Ko]], [[Chang-Shing Lee]], [[Shun-Feng Su]], [[Naoyuki Kubota]], and [[Takenori Obo]] (back row)<br/>
[[Lu-An Lin]] playing [[Go]] with [[DDF]], and the robot Palro reported real-time suggested next move to Lin
=PFML-based BCI Agent =
Abtract from ''PFML-based Semantic BCI Agent for Game of Go Learning and Prediction'' <ref>[[Chang-Shing Lee]], [[Mei-Hui Wang]], [[Li-Wei Ko]], [[Bo-Yu Tsai]], [[Yi-Lin Tsai]], [[Sheng-Chi Yang]], [[Lu-An Lin]], [[Yi-Hsiu Lee]], [[Hirofumi Ohashi]], [[Naoyuki Kubota]], [[Nan Shuo]] ('''2019'''). ''PFML-based Semantic BCI Agent for Game of Go Learning and Prediction''. [https://arxiv.org/abs/1901.02999 arXiv:1901.02999]</ref>:
This paper presents a semantic [https://en.wikipedia.org/wiki/Brain%E2%80%93computer_interface brain computer interface] (BCI) agent with [https://en.wikipedia.org/wiki/Particle_swarm_optimization particle swarm optimization] (PSO) based on a [https://en.wikipedia.org/wiki/Fuzzy_markup_language Fuzzy Markup Language] (FML) for [[Go]] [[Learning|learning]] and prediction applications. Additionally, we also establish an Open Go [https://en.wikipedia.org/wiki/Darkforest Darkforest] (OGD) cloud platform with Facebook AI research (FAIR) open source Darkforest and ELF OpenGo AI bots <ref>[https://ai.facebook.com/blog/open-sourcing-new-elf-opengo-bot-and-go-research/ Open-sourcing a new ELF OpenGo bot and related Go research], February 13, 2019</ref>. The Japanese robot Palro will simultaneously predict the move advantage in the board game Go to the Go players for reference or learning. The proposed semantic BCI agent operates efficiently by the human-based BCI data from their [https://en.wikipedia.org/wiki/Neural_oscillation brain waves] and machine-based game data from the prediction of the OGD cloud platform for optimizing the parameters between humans and machines. Experimental results show that the proposed human and smart machine co-learning mechanism performs favorably. We hope to provide students with a better online learning environment, combining different kinds of handheld devices, robots, or computer equipment, to achieve a desired and intellectual learning goal in the future.
=Selected Publications=
<ref>[https://dblp.uni-trier.de/pers/hd/k/Kubota:Naoyuki dblp: Naoyuki Kubota]</ref> <ref>[https://scholar.google.co.jp/citations?user=91umd98AAAAJ&hl=en Naoyuki Kubota - Google Scholar Citations]</ref>
* [[Chang-Shing Lee]], [[Mei-Hui Wang]], [[Chia-Hsiu Kao]], [[Sheng-Chi Yang]], [[Yusuke Nojima]], [[Ryosuke Saga]], [[Nan Shuo]], [[Naoyuki Kubota]] ('''2017'''). ''FML-based Prediction Agent and Its Application to Game of Go''. [https://arxiv.org/abs/1704.04719 arXiv:1704.04719]
* [[Chang-Shing Lee]], [[Mei-Hui Wang]], [[Sheng-Chi Yang]], [[Pi-Hsia Hung]], [[Su-Wei Lin]], [[Nan Shuo]], [[Naoyuki Kubota]], [[Chun-Hsun Chou]], [[Ping-Chiang Chou]], [[Chia-Hsiu Kao]] ('''2017'''). ''FML-based Dynamic Assessment Agent for Human-Machine Cooperative System on Game of Go''. [https://arxiv.org/abs/1707.04828 arXiv:1707.04828]
* [[Chang-Shing Lee]], [[Mei-Hui Wang]], [[Li-Wei Ko]], [[Naoyuki Kubota]], [[Lu-An Lin]], [[Shinya Kitaoka]], [[Yu-Te Wang]], [[Shun-Feng Su]] ('''2018'''). ''[https://www.semanticscholar.org/paper/Human-and-Smart-Machine-Co-Learning-with-Brain-Lee-Wang/0a06064108f2ad7319bc3ff0b37ccc6036d82f78 Human and Smart Machine Co-Learning with Brain Computer Interface]''. [https://arxiv.org/abs/1802.06521 arXiv:1802.06521]
* [[Chang-Shing Lee]], [[Mei-Hui Wang]], [[Li-Wei Ko]], [[Bo-Yu Tsai]], [[Yi-Lin Tsai]], [[Sheng-Chi Yang]], [[Lu-An Lin]], [[Yi-Hsiu Lee]], [[Hirofumi Ohashi]], [[Naoyuki Kubota]], [[Nan Shuo]] ('''2019'''). ''PFML-based Semantic BCI Agent for Game of Go Learning and Prediction''. [https://arxiv.org/abs/1901.02999 arXiv:1901.02999]
* [[Chang-Shing Lee]], [[Mei-Hui Wang]], [[Li-Chuang Chen]], [[Yusuke Nojima]], [[Tzong-Xiang Huang]], [[Jinseok Woo]], [[Naoyuki Kubota]], [[Eri Sato-Shimokawara]], [[Toru Yamaguchi]] ('''2019'''). ''A GFML-based Robot Agent for Human and Machine Cooperative Learning on Game of Go''. [https://arxiv.org/abs/1901.07191 arXiv:1901.07191]
=External Links=
* [https://researchmap.jp/read0124301/?lang=english KUBOTA Naoyuki - Researcher - researchmap]
* [http://www.comp.sd.tmu.ac.jp/kubota-lab/hp/member/member_en.htm Tokyo Metropolitan University KUBOTA laboratory]
* [https://scholar.google.co.jp/citations?user=91umd98AAAAJ&hl=en Naoyuki Kubota - Google Scholar Citations]
=References=
<references />
'''[[People|Up one level]]'''
[[Category:Researcher|Kubota]]
