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95
Voted
CG
2010
Springer
14 years 8 months ago
Biasing Monte-Carlo Simulations through RAVE Values
Abstract. The Monte-Carlo Tree Search algorithm has been successfully applied in various domains. However, its performance heavily depends on the Monte-Carlo part. In this paper, w...
Arpad Rimmel, Fabien Teytaud, Olivier Teytaud
84
Voted
INFORMATICALT
2000
104views more  INFORMATICALT 2000»
14 years 10 months ago
Nonlinear Stochastic Optimization by the Monte-Carlo Method
Methods for solving stochastic optimization problems by Monte-Carlo simulation are considered. The stoping and accuracy of the solutions is treated in a statistical manner, testing...
Leonidas Sakalauskas
AAAI
1998
14 years 11 months ago
Finding Optimal Strategies for Imperfect Information Games
Weexaminethree heuristic algorithms for gameswith imperfect information: Monte-carlo sampling, and two newalgorithms wecall vector minimaxingand payoffreduction minimaxing. Wecomp...
Ian Frank, David A. Basin, Hitoshi Matsubara
CG
2006
Springer
15 years 1 months ago
Monte-Carlo Proof-Number Search for Computer Go
In the last decade, proof-number search and Monte-Carlo methods have successfully been applied to the combinatorial-games domain. Proof-number search is a reliable algorithm. It re...
Jahn-Takeshi Saito, Guillaume Chaslot, Jos W. H. M...
ACG
2003
Springer
15 years 3 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
CIG
2006
IEEE
15 years 4 months ago
Monte-Carlo Go Reinforcement Learning Experiments
Abstract— This paper describes experiments using reinforcement learning techniques to compute pattern urgencies used during simulations performed in a Monte-Carlo Go architecture...
Bruno Bouzy, Guillaume Chaslot