Multi-agent Monte Carlo Go

@inproceedings{Marcolino2011MultiagentMC,
  title={Multi-agent Monte Carlo Go},
  author={Leandro Soriano Marcolino and Hitoshi Matsubara},
  booktitle={AAMAS},
  year={2011}
}
●The result is bad with all possible agents, so we try to add each one and test by experimentation Motivation ●Go is a strategic turn-based two-players board game ●Challenge for Artificial Intelligence ●Number of possible games is higher than the number of atoms in the known universe Multi-Agent Monte Carlo Go Leandro Soriano Marcolino and Hitoshi Matsubara Matsubara Laboratory – Intelligence Information Science Department Future University of Hakodate, Japan 

From This Paper

Topics from this paper.

Citations

Publications citing this paper.
Showing 1-10 of 10 extracted citations

References

Publications referenced by this paper.
Showing 1-10 of 34 references

Move decision method based on sds

  • T. Oguri, Y. Kotani
  • 14th Game Programming Workshop
  • 2009
Highly Influential
4 Excerpts

and T

  • T. Obata, T. Sugiyama, K. Hoki
  • Ito. Consultation algorithm in shogi: Can a set…
  • 2009
Highly Influential
5 Excerpts

Monte carlo go

  • B. Brugmann
  • Technical report, Physics Department, Syracuse…
  • 1993
Highly Influential
7 Excerpts

Systeme d’Apprentissage par Auto-Observation

  • T. Cazenave
  • Application au Jeu de Go. PhD thesis, Universite…
  • 1996
Highly Influential
5 Excerpts

Modelisation cognitive du joueur de Go

  • B. Bouzy
  • PhD thesis, Université Paris
  • 1995
Highly Influential
4 Excerpts

A pattern matcher for goliath

  • M. Boon
  • Computer Go, 13:13–23
  • 1990
Highly Influential
5 Excerpts

Similar Papers

Loading similar papers…