Naoyuki Kubota

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Naoyuki Kubota, a Japanese engineer, researcher in the field of robotics and computational intelligence, and professor at the Tokyo Metropolitan University and head of the Kubota laboratory. He received a Ph.D. in engineering from Nagoya University in 1997. His recent research includes human and smart machine co-learning with the Brain-computer interface, also applied to Go playing.

=Co-Learning with BCI= Abtract from Human and Smart Machine Co-Learning with Brain Computer Interface Machine learning has become a very popular approach for cybernetics systems, and it has always been considered important research in the 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) Darkforest program of Facebook with 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 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= Li-Wei Ko, Chang-Shing Lee, Shun-Feng Su, Naoyuki Kubota, and Takenori Obo (back row) 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 : This paper presents a semantic brain computer interface (BCI) agent with particle swarm optimization (PSO) based on a Fuzzy Markup Language (FML) for Go learning and prediction applications. Additionally, we also establish an Open Go Darkforest (OGD) cloud platform with Facebook AI research (FAIR) open source Darkforest and ELF OpenGo AI bots. 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 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=
 * 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. 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. 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). Human and Smart Machine Co-Learning with Brain Computer Interface. 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. 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. arXiv:1901.07191

=External Links=
 * KUBOTA Naoyuki - Researcher - researchmap
 * Tokyo Metropolitan University KUBOTA laboratory
 * Naoyuki Kubota - Google Scholar Citations

=References= Up one level