IEEE Systems, Man and Cybernetics Magazine - January 2020 - 31

team from moves 172 and 171, respectively. The middle
game shows that move 171 was a key move because the
white team remained the winner, although Lee (8p) followed the top suggested moves to play after move 171. The
right-hand game presented in Figure 9 indicates that the
black team finally won the game when Lee (8p) started to
follow the robot's top suggested move from move 171.
The main contributions of this article are insights into
how machines and humans can co-learn using the following two technologies:
1) a machine-human co-learning model that helps human
game players to learn and analyze a game (specifically
focused on the game Go in this case) based on their
learning behavior and performance
2) a novel wearable BCI system that monitors the physiological states of a game player to enable evaluation of
human learning progress.
In the future, we will combine different types of mobile
devices, robots, and computer devices with our developed
platform. Hopefully, the platform will provide students
with a better online learning environment to achieve the
goal of learning without borders.
Acknowledgments
The event at IEEE SMC 2018 was a great success, and we
would like to express our heartfelt thanks to everyone who
offered help, joined, or watched the games and the BCI-OGD
demonstration. We would also like to sincerely thank the
IEEE SMCS and the Organizing Committee of IEEE SMC
2018, especially General Chair Yutaka Hata and Program
Chair Tadahiko Murata. We would like to thank the Ministry of Science and Technology of Taiwan (MOST 107-2218-E024-001), IEEE SMCS's outreach project, and Shen-Su
Chang (HeroIT.com Co. Ltd., New Tapei City, Taiwan) for
their financial support, and The Asahi Shimbun for approving use of the seventh game of the 2018 Japanese Meijin Go
Tournament as an example of human-smart machine colearning. Finally, we would like to thank National Tainan
First High School, all of the Go players (Chun-Hsun Chou,
Kai-Hsin Chang, Maki Kaneko, Hideki Kato, and the other
amateur Go players), Sheng-Chi Yang, the Taiwanese government, National Center for High-performance Computing
of Taiwan, Kaname Tsukioka from Fujisoft, and Osaka Prefecture University for supporting this special event.

ty, Taoyuan City, Taiwan, and her M.S. degree in electrical engineering from the Yuan Ze University, Taiwan, in 1995. She is a
researcher with the Ontology Applications & Software Engineering Laboratory, National University of Tainan, Taiwan.
Li-Wei Ko (lwko@mail.nctu.edu.tw) earned his undergraduate degree from the National Chung Cheng University,
Minxiong, Chiayi, Taiwan, his graduate degree from the
National Taichung University of Education, Taiwan, and his
Ph.D. degree in electrical engineering from National Chiao
Tung University, Hsinchu City, Taiwan, in 2007. He is an associate professor with the Institute of Bioinformatics and Systems Biology, National Chiao Tung University.
Yi-Hsiu Lee (good-luck0616@hotmail.co.jp) is an
8p-ranked professional Go player of the Japan Go
Association.
Hirofumi Ohashi (xsp7top@yahoo.co.jp) is a
6p-ranked professional Go player of the Japan Go Association. He is also an organizer of Project Go AI with Go players and software developers.
Naoyuki Kubota (kubota@tmu.ac.jp) earned his graduate degree from Hokkaido University, Japan, and his D.E.
degree from Nagoya University, Japan, in 1997. He is a professor in the Department of System Design, Tokyo Metropolitan University, Tokyo, Japan.
Yusuke Nojima (nojima@cs.osakafu-u.ac.jp) earned his
undergraduate and graduate degrees from the Osaka Institute
of Technology, Japan, and his Ph.D. degree in system function science from Kobe University, Japan, in 2004. He is an
associate professor in the Department of Computer Science
and Intelligent Systems, Osaka Prefecture University, Japan.
Shun-Feng Su (su@orion.ee.ntust.edu.tw) earned his
undergraduate and graduate degrees from the National Taiwan University, Taipei City, and his Ph.D. degree in electrical engineering from Purdue University, West Lafayette,
Indiana, in 1991. He is a professor in the Department of
Electrical Engineering, National Taiwan University of Science and Technology.
References
[1] D. Silver et al., "Mastering the game of Go with deep neural networks and tree
search," Nature, vol. 529, no. 7587, pp. 484-489, Jan. 2016.
[2] Y. Tian and Y. Zhu, "Better computer Go player with neural network and long-term
prediction," in Proc. 2016 Int. Conf. Learning Representations (ICLR 2016), San Juan,
Puerto Rico, May 2-4, 2016. [Online]. Available: arXiv:1511.06410
[3] Y. Tian and L. Zitnick, "Facebook open sources ELF OpenGo," Facebook Research,

About the Authors
Chang-Shing Lee (leecs@mail.nutn.edu.tw) earned his
undergraduate degree from the Chung Yuan Christian University, Taoyuan City, Taiwan, and his graduate degree and
Ph.D. degree in computer science and information engineering from the National Cheng Kung University, Tainan, Taiwan, in 1998. He is currently a professor with the Department of Computer Science and Information Engineering,
National University of Tainan, Taiwan.
Mei-Hui Wang (mh.alice.wang@gmail.com) earned her
undergraduate degree from the Chung Yuan Christian Universi-

May 2018. [Online]. Available: https://research.fb.com/facebook-open-sources-elf
-opengo/
[4] "Human & smart machine co-learning @ IEEE SMC 2018," OASE Laboratory,
Taiwan, Oct. 7, 2018, [Online]. Available: http://oase.nutn.edu.tw/IEEESMC2018
[5] "Collection of photos of human & smart machine co-learning @ IEEE SMC
2018," OASE Laboratory, Taiwan, Oct. 14, 2018, [Online]. Available: https://youtu.be/
kW6W5JCbKmg
[6] "The 7th game between Chang Hsu and Yuta Iyama, 2018 Japanese Meijin Go Tournament," The Asahi Shimbun, Dec. 2018, [Online]. Available: http://www.asahi.com/
igo/meijin/PND43_7ban07_a14.html

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https://research.fb.com/facebook-open-sources-elf-opengo/ http://oase.nutn.edu.tw/IEEESMC2018 https://www.youtube.com/watch?v=kW6W5JCbKmg&feature=youtu.be https://www.youtube.com/watch?v=kW6W5JCbKmg&feature=youtu.be http://www.asahi.com/igo/meijin/PND43_7ban07_a14.html http://www.asahi.com/igo/meijin/PND43_7ban07_a14.html

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