Presentation	2011-03-28 Monte-Carlo Go Based on a Gaussian Process Shuichi FUKUNAGA, Hikaru ARAI,
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Abstract(in English)	Recently, a tree search algorithm using a Gaussian process which applied Gaussian Process Bandits (GPB) to a Monte-Carlo tree search was proposed. It has a better performance than former methods. This paper proposes a Monte- Carlo go based on the tree search algorithm using the Gaussian process. The proposed method employs a strategy which maximizes a upper confidence function using a covariance matrix and a kernel function in the Gaussian process. Numerical simulations show the effectiveness of the proposed method.
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Keyword(in English)	Computer Go / Gaussian Processes / Monte-Carlo Tree Search
Paper #	IBISML2010-106
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Conference Information
Committee	IBISML
Conference Date	2011/3/21(1days)
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Paper Information
Registration To	Information-Based Induction Sciences and Machine Learning (IBISML)
Language	JPN
Title (in Japanese)	(See Japanese page)
Sub Title (in Japanese)	(See Japanese page)
Title (in English)	Monte-Carlo Go Based on a Gaussian Process
Sub Title (in English)
Keyword(1)	Computer Go
Keyword(2)	Gaussian Processes
Keyword(3)	Monte-Carlo Tree Search
1st Author's Name	Shuichi FUKUNAGA
1st Author's Affiliation	Tokyo Metropolitan College of Industrial Technology()
2nd Author's Name	Hikaru ARAI
2nd Author's Affiliation	Tokyo Metropolitan College of Industrial Technology
Date	2011-03-28
Paper #	IBISML2010-106
Volume (vol)	vol.110
Number (no)	476
Page	pp.pp.-
#Pages	5
Date of Issue