Learning to Predict Life and Death from Go Game Records

Abstract

This paper presents a learning system for predicting life and death in the game of Go. Learning examples are extracted from game records. On average our system correctly predicts life and death for 88% of all blocks. Towards the end of a game the performance increases up to 99%. Clearly, such a predictor will be an important component for building a full-board evaluation function.