NUTN, Taiwan
Co-sponsors Co. Ltd.

Scope and Topics

(1)To integrate the open source FAIR Darkforest (DF) program of Facebook (USA) with Item Response Theory (IRT) of NUTN (Taiwan) to the new open Go system, namely Dynamic DF (DyNaDF, Dynamic Darkforest) Go system; (2) To integrate DyNaDF Go with FujiSoft Robot of TMU (leading by Prof. Kubota Lab., Japan) namely Robotic DyNaDF Go system; (3) To invite three professional Go players (9P / Taiwan, 6P / Japan, and 6P / Taiwan) to attend the activity to have Go game on site with machine; (4) To have a workshop in IEEE SMC 2017 to call for submissions from related researchers; (5) To have special issues in some journals to attract more attentions of researchers

Activity Format

(1) To have an Activity on “Human Interactive Learning on Cybernetics” in IEEE SMC 2017; (2) To invite speakers; (3) To have three activities for “Robotic Open Go System for Human Interactive Learning on Cybernetics” on site of IEEE SMC 2017.
Robotic DyNaDF Go + 6P / Taiwan vs. Robotic DyNaDF Go + 9P / Taiwan
Robotic DyNaDF Go + 6P / Japan vs. Robotic DyNaDF Go + 9P / Taiwan
Robotic DyNaDF Go + 6P / Taiwan vs. Robotic DyNaDF Go + 6P / Japan 

Importance of Activity

Learning has become a very popular approach for cybernetics systems. This topic has always been considered a research in the Computational Intelligence area. Nevertheless, when talking about smart machines, it is not just about the methodologies. We need to consider systems and cybernetics. Sometimes, we also need to include human in the loop. Thus, it is definitely a research topic in SMC Society. Rémi Coulom, a freelance developer of Go programs, said "Online games are usually played at a faster pace, which favours the computer over humans," and he still expected a strong correlation with performance in serious slow tournament games. Hence, we need to have a workshop, "Human Interactive Learning on Cybernetics," and have Go games on site not just like others playing through internet in IEEE SMC 2017. Attract more scholars in this area to join SMC conference and then join the SMC society. Smart machine is the main theme of IEEE SMC 2017. It is good to use this competition of Professional Players vs. Machine and also have some cooperation between them to attract more attentions of worldwide scholars to SMC conferences.

History of Activity

The year is the first year to hold Human & Smart Machines Co-Learning @ IEEE SMC 2017. But for the human vs. computer Go competitions, the organizers have been held since 2008. For more details, you can refer to this video about the activities of Human vs. Computer Go from 2008 to 2016 funded by IEEE CIS, Taiwan government, National University of Tainan (NUTN) and Taiwanese Association for Artificial Intelligence (TAAI), Taiwan. The handicaps for the human vs. computer 19×19 game have been decreased from 29 in 1998 to 0 in 2016.
Standard Definition: 2008-2016 Human vs. Computer Go Video
High Definition: 2008-2016 Human vs. Computer Go Video
Past activities of Human vs. Computer Go from 2008 to 2016: Human vs. Computer Go

Expected Humans

Professional Go Players
- Chun-Hsun Chou (9P / Taiwan)
- Ping-Chiang Chou (6P / Taiwan)
- Kai-Hsin Chang (5P / Taiwan)
- Lu-An Lin (6D / Taiwan)
- Daisuke Horie (4D / Japan)
- Shuji Takemura (1D / Japan)

Expected Computer Go Programs
- Darkforest Open Source (DDF)
- Deep Zen Go
Download File
- Brief introduction to Human & Smart Machine Co-Learning



CCS, Japan

MOST, Taiwan

NCTU, Taiwan

NEL/NCTU, Taiwan



Hifong Weiqi Academy

Bureau of Education

Bureau of Education

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