Computational Intelligence - August 2016 - 67
Discussion
Forum
Chang-Shing Lee and Mei-Hui Wang
Department of Computer Science and Information
Engineering, National University of Tainan, TAIWAN
Shi-Jim Yen
Department of Computer Science and Information
Engineering, National Dong Hwa University, TAIWAN
Ting-Han Wei and I-Chen Wu
Department of Computer Science, 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
Human vs. Computer Go: Review and Prospect
Abstract
T
he 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. Commentaries
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.
image licensed by graphic stock
The IEEE Computational Intelligence
Society (CIS) has funded human vs. com-
puter Go competitions in IEEE CIS flagship conferences since 2009. Fig. 1 shows
the year and the location of the conferences. The descriptions of competitions
held from 1998 to 2016 are listed in detail
in an online version of this article [1]-[8].
The handicaps for the human vs. computer 19 # 19 game have been decreased
from 29 in 1998 to 0 in 2016. The skill of
amateur players in Go is ranked according
to kyu (K) in the lower tier, where a smaller number stands for stronger playing skill
(with 1K being the highest skill level), and
dan (D) in the higher tier, where a larger
number stands for stronger playing skill.
Digital Object Identifier 10.1109/MCI.2016.2572559
Date of publication: 18 July 2016
Corresponding author: Chang-Shing Lee (E-mail:
leecs@mail.nutn.edu.tw).
I. Computer Go Competitions
1556-603x/16©2016ieee
Professional Go players are ranked entirely
in dan, abbreviated with the letter P (e.g.
Lee Sedol is ranked at 9P). In the amateur
level, each difference in rank roughly
translates to a single stone of handicap (H),
where the weaker player is allowed to
place an additional stone on the board
prior to play to even out the game. The
skill difference between professional ranks
is much less than one stone for every rank
difference. Go is typically played on
19 # 19 size boards, but 9 # 9 size boards
are also common for beginners.The complexity of the 9 # 9 game is far less than
the standard game, and the 9 # 9 game
had been one of the interim goals for
computer Go programs. Go is a game that
is inherently biased for the first player to
play, Black. To compensate for this first
player advantage, White is awarded additional points at the end of the game,
which is referred to as komi. The related
statistics for the IEEE CIS human vs.
computer Go competitions are listed in
the online version of this article [8]. It is
worth noting that with a komi of 7.5,
White may end up with an advantage in
both 9 # 9 games and handicapped
19 # 19 games, regardless of whether
White is played by humans or computers.
Fig. 2 shows the certificate awarded to the
MoGoTW program (16 cores/ 48 GB/
AUGUst 2016 | IEEE Computational intelligence magazine
67
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Computational Intelligence - August 2016 - Cover1
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