Two-Stage Monte Carlo Tree Search for Connect6

Recently, Monte Carlo tree search (MCTS) has become a well-known game search method, and has been successfully applied to many games. This method performs well in solving search trees with numerous branches, such as Go, Havannah, etc. Connect6 is a game involving a search tree with numerous branches...

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Bibliographic Details
Published in:IEEE transactions on computational intelligence and AI in games. Vol. 3; no. 2; pp. 100 - 118
Main Authors: Yen, Shi-Jim, Yang, Jung-Kuei
Format: Journal Article
Language:English
Published: IEEE 01.06.2011
Subjects:
Algorithms
Artificial intelligence
Board games
Connect6
conservative TSS
Estimates
Games
Intelligence
Iterative algorithm
iterative TSS
Law
Monte Carlo methods
Monte Carlo tree search
Search methods
Searching
threat space search
Trees
Vegetation
ISSN:1943-068X, 1943-0698
Online Access:Get full text
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Summary:Recently, Monte Carlo tree search (MCTS) has become a well-known game search method, and has been successfully applied to many games. This method performs well in solving search trees with numerous branches, such as Go, Havannah, etc. Connect6 is a game involving a search tree with numerous branches, and it is also one of the sudden-death games. This paper thus proposes a new MCTS variant related to Connect6, called two-stage MCTS. The first stage focuses on threat space search (TSS), which is designed to solve the sudden-death problem. For the double-threat TSS in Connect6, this study proposes an algorithm called iterative threat space search (ITSS) which combines normal TSS with conservative threat space search (CTSS). The second stage uses MCTS to estimate the game-theoretic value of the initial position. This stage aims at finding the most promising move. The experimental result shows that two-stage MCTS is considerably more efficient than traditional MCTS on those positions with TSS solution in Connect6. Furthermore, according to Connect6 heuristic knowledge, this paper uses relevance-zone search to accelerate identifying winning and losing moves.
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ISSN:1943-068X
1943-0698
DOI:10.1109/TCIAIG.2011.2134097