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ACG
2003
Springer
13 years 10 months ago
Monte-Carlo Go Developments
We describe two Go programs,  ¢¡¤£¦¥ and  ¢¡¤§¨£ , developed by a Monte-Carlo approach that is simpler than Bruegmann’s (1993) approach. Our method is based on Abra...
Bruno Bouzy, Bernard Helmstetter
ICML
2009
IEEE
14 years 5 months ago
Monte-Carlo simulation balancing
In this paper we introduce the first algorithms for efficiently learning a simulation policy for Monte-Carlo search. Our main idea is to optimise the balance of a simulation polic...
David Silver, Gerald Tesauro
ACG
2009
Springer
13 years 11 months ago
Monte-Carlo Tree Search in Settlers of Catan
Abstract. Games are considered important benchmark tasks of artificial intelligence research. Modern strategic board games can typically be played by three or more people, which m...
Istvan Szita, Guillaume Chaslot, Pieter Spronck
AAAI
2006
13 years 6 months ago
Monte Carlo Go Has a Way to Go
Monte Carlo Go is a promising method to improve the performance of computer Go programs. This approach determines the next move to play based on many Monte Carlo samples. This pap...
Haruhiro Yoshimoto, Kazuki Yoshizoe, Tomoyuki Kane...
ACG
2006
Springer
13 years 10 months ago
A Phantom-Go Program
Abstract. This paper presents a Phantom Go program. It is based on a MonteCarlo approach. The program plays Phantom Go at an intermediate level.
Tristan Cazenave