Human vs. Computer Go: Review and Prospect @ IEEE CIS

The online version can be downloaded from here (CIM201603001(Revised)-04222016).

The accepted version can be downloaded from here (CIM201603001(Accepted)-05202016-6).

Human vs. Computer Go: Review and Prospect @ IEEE CIS

Integrated Human and Computational Intelligence for Future Go Learning

based on Google AlphaGo’s Historic Achievement


Chang-Shing Lee and Mei-Hui Wang, National University of Tainan, Taiwan

Shi-Jim Yen, National Dong Hwa University, Taiwan

Ting-Han Wei and I-Chen Wu, National Chiao Tung University, Taiwan

Ping-Chiang Chou and Chun-Hsun Chou, Taiwan Go Association, Taiwan

Ming-Wan Wang, Nihon Ki-in Go Institute, Japan

Tai-Hsiung Yang, Haifong Weiqi Academy, Taiwan


Abstract

The Google DeepMind challenge match in March 2016 was a historic achievement for computer Go development. This article discusses the development of computational intelligence (CI) and its relative strength in comparison with human intelligence for the game of Go. We first summarize the milestones achieved for computer Go from 1998 to 2016. Then, the computer Go programs that have participated in previous IEEE CIS competitions as well as methods and techniques used in AlphaGo are briefly introduced. Commentary from three high-level professional Go players on the five AlphaGo versus Lee Sedol games are also included. We conclude that AlphaGo beating Lee Sedol is a huge achievement in artificial intelligence (AI) based largely on CI methods. In the future, powerful computer Go programs such as AlphaGo are expected to be instrumental in promoting Go education and AI real-world applications.