Search versus Knowledge for Solving Life and Death Problems in Go

摘要

In games research, Go is considered the classical board game that is most resistant to current AI techniques. Large-scale knowledge engineering has been considered indispensable for building state of the art programs, even for subprob-lems such as Life and Death, or tsume-Go. This paper describes the technologies behind TSUMEGO EXPLORER, a high-performance tsume-Go search engine for enclosed problems. In empirical testing, this engine outperforms GoTools, which has been the undisputedly best tsume-Go program for 15 years.