Searching with probabilities
Game tree searching by min/max approximation
Artificial Intelligence
Expected-Outcome: A General Model of Static Evaluation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Artificial Intelligence
A Bayesian approach to relevance in game playing
Artificial Intelligence - Special issue on relevance
Computer Go: an AI oriented survey
Artificial Intelligence
A study of decision error in selective game tree search
Information Sciences: an International Journal - Heuristic Search and Computer Game Playing
Artificial Intelligence - Chips challenging champions: games, computers and Artificial Intelligence
World-championship-caliber Scrabble
Artificial Intelligence - Chips challenging champions: games, computers and Artificial Intelligence
Monte Carlo go has a way to go
AAAI'06 proceedings of the 21st national conference on Artificial intelligence - Volume 2
Monte-Carlo proof-number search for computer Go
CG'06 Proceedings of the 5th international conference on Computers and games
Virtual global search: application to 9×9 Go
CG'06 Proceedings of the 5th international conference on Computers and games
Efficient selectivity and backup operators in Monte-Carlo tree search
CG'06 Proceedings of the 5th international conference on Computers and games
Move-Pruning techniques for monte-carlo go
ACG'05 Proceedings of the 11th international conference on Advances in Computer Games
Solving probabilistic combinatorial games
ACG'05 Proceedings of the 11th international conference on Advances in Computer Games
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This paper explores the association of shallow and selective global tree search with Monte Carlo in 9 × 9 Go. This exploration is based on Olga and Indigo, two experimental Monte-Carlo programs. We provide a min-max algorithm that iteratively deepens the tree until one move at the root is proved to be superior to the other ones. At each iteration, random games are started at leaf nodes to compute mean values. The progressive pruning rule and the min-max rule are applied to non terminal nodes. We set up experiments demonstrating the relevance of this approach. Indigo used this algorithm at the 8th Computer Olympiad held in Graz.