A Comparison of Monte-Carlo Methods for Phantom Go

@inproceedings{Borsboom2007ACO,
  title={A Comparison of Monte-Carlo Methods for Phantom Go},
  author={Joris Borsboom and Jahn-Takeshi Saito and Guillaume Chaslot and Jos W. H. M. Uiterwijk},
  year={2007}
}
Throughout recent years, Monte-Carlo methods have considerably improved computer Go programs. In particular, Monte-Carlo Tree Search algorithms such as UCT have enabled significant advances in this domain. Phantom Go is a variant of Go which is complicated by the condition of imperfect information. This article compares four Monte-Carlo methods for Phantom Go in a self-play experiment: (1) Monte-Carlo evaluation with standard sampling, (2) MonteCarlo evaluation with all-as-first sampling, (3… CONTINUE READING
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Grouping Nodes for Monte-Carlo Tree Search

  • Jahn-Takeshi Saito, Mark H.M. Winands, Jos W.H.M. Uiterwijk, H. Jaap van den Herik
  • In Jos W.H.M. Uiterwij,
  • 2007
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