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Title:
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DETECTING THE COMMUNITY STRUCTURES IN THE GAME OF GO |
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Author(s):
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Yuri Malitsky , Christopher Fellows , Gregory Wojtaszczyk |
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ISBN:
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978-972-8924-40-9 |
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Editors:
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Jörg Roth, Jairo Gutiérrez and Ajith P. Abraham (series editors: Piet Kommers, Pedro Isaías and Nian-Shing Chen) |
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Year:
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2007 |
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Edition:
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Single |
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Keywords:
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Clustering, Interaction Network, Computer Go |
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Type:
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Short Paper |
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First Page:
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135 |
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Last Page:
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139 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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Go is a complex board game that stands impervious to the present computational intelligence. This project continues our
composite approach, aiming to integrate the strengths of proven heuristic algorithms with AI techniques for boosting
performance of Computer Go. In previous research, we explored Support Vector Machine (SVM) supervised training of a
move evaluation function based on a collection of expert games. In this paper, we present a graph-based model for
describing the board position and an application of Newman-Girvan edge betweenness clustering algorithm for detecting
the Go dragons, communities of loosely connected stones. |
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