COMPUTING “ELO RATINGS” OF MOVE PATTERNS IN THE GAME OF GO

Rémi Coulom · ICGA Journal · 2007

Summary

A new Bayesian technique for supervised learning of move patterns from game records based on a generalization of Elo ratings, which outperforms most previous pattern-learning algorithms, both in terms of mean log-evidence and prediction rate.

Type: article
Published: 2007-12-01
Cited by: 363
References: 20
Access: Open access
DOI: https://doi.org/10.3233/icg-2007-30403
OpenAlex: https://openalex.org/W1500868819
Semantic Scholar: https://api.semanticscholar.org/CorpusID:5733047

Keywords

Computer science

References

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Move Prediction in Go with the Maximum Entropy MethodNobuo Araki, Kazuhiro YOSHIDA, Yoshimasa Tsuruoka — 2007
Associating domain-dependent knowledge and Monte Carlo approaches within a Go programBruno Bouzy — 2005
Bayesian pattern ranking for move prediction in the game of GoDavid Stern, Ralf Herbrich, Thore Graepel — 2006
MM algorithms for generalized Bradley-Terry modelsDavid R. Hunter — 2003
Iterative WideningTristan Cazenave — 2001
Modification of UCT with Patterns in Monte-Carlo GoS. Gelly, Yizao Wang, R. Munos — 2006
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Modiﬁcation of UCT with Patterns in Monte-Carlo GoSylvain Gelly, Yizao Wang, Rémi Munos — 2006
TrueSkillTM: A Bayesian Skill Rating SystemR. Herbrich, T. Minka, T. Graepel — 2006
Efficient Selectivity and Backup Operators in Monte-Carlo Tree SearchRémi Coulom — 2006

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COMPUTING “ELO RATINGS” OF MOVE PATTERNS IN THE GAME OF GO

Summary

Keywords

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