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CIG
2006
IEEE
13 years 11 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
ICAI
2009
13 years 3 months ago
All-Moves-As-First Heuristics in Monte-Carlo Go
Abstract-- We present and explore the effectiveness of several variations on the All-Moves-As-First (AMAF) heuristic in Monte-Carlo Go. Our results show that:
David P. Helmbold, Aleatha Parker-Wood
CG
2006
Springer
13 years 9 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...
CIG
2005
IEEE
13 years 11 months ago
Combining Tactical Search and Monte-Carlo in the Game of Go
We present a way to integrate search and Monte-Carlo methods in the game of Go. Our program uses search to find the status of tactical goals, builds groups, selects interesting go...
Tristan Cazenave, Bernard Helmstetter
ACG
2006
Springer
13 years 11 months ago
Move-Pruning Techniques for Monte-Carlo Go
Abstract. Progressive Pruning (PP) is used in the Monte-Carlo go playing program Indigo. For each candidate move, PP launches random games starting with this move. PP gathers stati...
Bruno Bouzy