Search versus knowledge for solving life and death problems in Go

Authors:
Akihiro Kishimoto;Martin Müller
Affiliations:
Department of Media Architecture, Future University-Hakodate, Hakodate, Hokkaido, Japan;Department of Computing Science, University of Alberta, Edmonton, Canada
Venue:
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 3
Year:
2005

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Abstract

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 subproblems 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.