News Archives

[Colloquium] Recent Advances in Computer Go Playing

September 7, 2012

Watch Colloquium: 

M4V file (585 MB)

  • Date: Friday, September 7, 2012 
  • Time: 12:00 pm — 12:50 pm 
  • Place: Centennial Engineering Center 1041

Patrick Bridges
Department of Computer Science University of New Mexico 

The oriental board game Go (Chinese: Wei’qi, Korean: Baduk, Japanese: Igo) has long been of one of the most challenging board games for computers to play. For example, computers are as strong or stronger than the best human players, backgammon programs play at world championship levels, and checkers is actually solved. In contrast, computer Go programs have long been at best no stronger than an average club player. This is no longer true. Relatively recent advances in computer Go programs have resulted in dramatic advances in computer strength. Computers can now hold their own against professional players on reduced-size 9×9 boards, and hold their own and beat reasonably strong (amatuer dan-level) human players.

In this talk, I describe why Go has historically been difficult for computers to play well and the recent technical advances that have enabled the large increases in computer Go program strength. As part of this, I will also overview the basics of the game itself, and present some recent examples of the growth in computer strength (including one that involved a $10,000 bet). Finally, I will discuss both the future prospects of computer Go play, and the broader relevance of the techniques used to make strong computer Go programs to computer science in general.


Bio: Patrick Bridges is an associate professor at the University of New Mexico in the Department of Computer Science. He did his undergraduate work at Mississippi State University and received his Ph.D. from the University of Arizona in December of 2002. His research interest broadly cover operating systems and networks particularly, scaling, composition, and adaptation issues in large-scale systems. He works with collaborators at Sandia, Los Alamos, and Lawrence Berkeley National Laboratories, IBM Research, AT&T Research, and a variety of universities.