Learning to score final positions in the game of go

Abstract

This paper presents a learning system for scoring final positions in the Game of Go. Our system leams to predict life and death from labelled game records. 98.9% of the positions are scored correctly and nearly all incorrectly scored positions are recognized. By providing reliable score information our system opens the large source of Go knowledge implicitly available in human game records, thus paving the way for a successful application of machine learning in Go. © 2004 by Springer Science+Business Media New York.