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Please use this identifier to cite or link to this item: http://hdl.handle.net/10119/13831

Title: Machine-Learning of Shape Names for the Game of Go
Authors: Ikeda, Kokolo
Shishido, Takanari
Viennot, Simon
Keywords: Go
Machine Learning
Shape Name
Issue Date: 2015-12-25
Publisher: Springer
Magazine name: Lecture Notes in Computer Science
Volume: 9525
Start page: 247
End page: 259
DOI: 10.1007/978-3-319-27992-3_22
Abstract: Computer Go programs with only a 4-stone handicap have recently defeated professional humans. Now that the strength of Go programs is sufficiently close to that of humans, a new target in artificial intelligence is to develop programs able to provide commentary on Go games. A fundamental difficulty in this development is to learn the terminology of Go, which is often not well defined. An example is the problem of naming shapes such as Atari, Attachment or Hane. In this research, our goal is to allow a program to label relevant moves with an associated shape name. We use machine learning to deduce these names based on local patterns of stones. First, strong amateur players recorded for each game move the associated shape name, using a pre-selected list of 71 terms. Next, these records were used to train a supervised machine learning algorithm. The result is a program able to output the shape name from the local patterns of stones. Including other Go features such as change in liberties improved the performance. Humans agreed on a shape name with a rate of about 82 %. Our algorithm achieved a similar performance, picking the name most preferred by the humans with a rate of about 82 %. This performance is a first step towards a program that is able to communicate with human players in a game review or match.
Rights: This is the author-created version of Springer, Kokolo Ikeda, Takanari Shishido, and Simon Viennot, Lecture Notes in Computer Science, 9525, 2015, 247-259. The original publication is available at www.springerlink.com, http://dx.doi.org/10.1007/978-3-319-27992-3_22
URI: http://hdl.handle.net/10119/13831
Material Type: author
Appears in Collections:b11-1. 会議発表論文・発表資料 (Conference Papers)

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