Depth-first iterative-deepening: an optimal admissible tree search
Artificial Intelligence
The History Heuristic and Alpha-Beta Search Enhancements in Practice
IEEE Transactions on Pattern Analysis and Machine Intelligence
Artificial Intelligence
An analysis of forward pruning
AAAI'94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 2)
ACM '86 Proceedings of 1986 ACM Fall joint computer conference
CG '08 Proceedings of the 6th international conference on Computers and Games
Journal of Artificial Intelligence Research
A new heuristic search algorithm for capturing problems in Go
CG'06 Proceedings of the 5th international conference on Computers and games
Theoretical Computer Science
Improving Monte-Carlo tree search in Havannah
CG'10 Proceedings of the 7th international conference on Computers and games
Dual lambda search and shogi endgames
ACG'05 Proceedings of the 11th international conference on Advances in Computer Games
A new family of k-in-a-row games
ACG'05 Proceedings of the 11th international conference on Advances in Computer Games
Searching for compound goals using relevancy zones in the game of go
CG'04 Proceedings of the 4th international conference on Computers and Games
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We propose a method to gradually expand the moves to consider at the nodes of game search trees. The algorithm is an extension of Abstract Proof Search, an algorithm that solves more problem than basic Alpha-Beta search in less time and which is more reliable. Unlike other related algorithms, iterative winding adapts to the game via genearal game definition functions. In the game of Go, it can solve more problems than the original non windening algorithm in approximately half of the time, as shown by the experimental results.