Abstract
Patterns are an essential method to improve the performance of computer Go programs. Machine learning algorithms for pattern extraction and evaluation are eternal topics for the study of computer Go programs. This paper presents a new machine learning algorithm to extract and evaluate contextual Go patterns with an Elo rating system. This algorithm calculates the Elo rating of a contextual pattern by comparing it with patterns within a certain contextual area insetad of the whole board. Not only produce a more accurate evaluation of Go patterns, this algorithm also reduces the time complexity significantly. Experiment results indicate that Go pattern evaluations produced by the new algorithm result in stronger performance when used in simulation of Monte-Carlo Tree Search.
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