2014
DOI: 10.1007/978-3-319-13560-1_39
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K-means Pattern Learning for Move Evaluation in the Game of Go

Abstract: Abstract. The Game of Go is one of the biggest challenge in the field of Computer Game. The large board makes Go very complex and hard to evaluate. In this paper, we propose a method that reduce the complexity of Go by learning and extracting patterns from game records. This method is more efficient and stronger than the baseline method we have chosen. Our method has two major components: a) a pattern learning method based on K-means, it will learn and extract patterns from game records, b) a perceptron which … Show more

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Cited by 2 publications
(1 citation statement)
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“…The problem of learning and developing a program that could develop on its own in Grae-go, selfcomplacent is one of the strongest motivations of programmers. One of the methods of developing programs and approaching artificial intelligence was done by Liang, and Chen (2014). In this article, the authors propose a method that reduces the complexity of the Go game by studying and extracting patterns from game records.…”
mentioning
confidence: 99%
“…The problem of learning and developing a program that could develop on its own in Grae-go, selfcomplacent is one of the strongest motivations of programmers. One of the methods of developing programs and approaching artificial intelligence was done by Liang, and Chen (2014). In this article, the authors propose a method that reduces the complexity of the Go game by studying and extracting patterns from game records.…”
mentioning
confidence: 99%