PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

SVM and Pattern-Enriched Common Fate Graphs for the Game of Go
Liva Ralaivola, Lin Wu and Pierre Baldi
In: ESANN 2005, 27-29 Apr 2005, Bruges, Belgium.

Abstract

We propose a pattern-based approach combined with the concept of Enriched Common Fate Graph for the problem of classifying Go positions. A kernel function for weighted graphs to compute the similarity between two board positions is proposed and used to learn a support vector machine and address the problem of position evaluation. Numerical simulations are carried out using a set of human played games and show the relevance of our approach.

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EPrint Type:Conference or Workshop Item (Oral)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Computational, Information-Theoretic Learning with Statistics
ID Code:1460
Deposited By:Liva Ralaivola
Deposited On:28 November 2005