Sciweavers

CG
2010
Springer
13 years 9 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
INFORMATICALT
2000
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13 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 7 days 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
14 years 2 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
14 years 4 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
14 years 5 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