UCT
UCT (Upper Confidence bounds applied to Trees) is the most commonly used tree policy in MCTS. It applies the UCB1 formula from multi-armed bandit problems to the selection of tree nodes, balancing exploration and exploitation during the search.
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UCT (Upper Confidence bounds applied to Trees) is the most commonly used tree policy in MCTS, and its core idea is to apply the UCB1 formula from multi-armed bandits to tree node selection.
Under conditions of infinite sampling and appropriate decay of the exploration parameter, UCT-type algorithms can converge to the optimal solution of the game tree, but this conclusion relies on idealized assumptions such as the simulation policy being able to cover all actions and rewards being bounded.
PUCT 在每次选择节点时，除了利用 UCT 的探索-利用权衡项，还引入了一个基于策略网络的先验预测项，用来指导搜索往更有希望的分支扩展。
All Facts (3)
UCT (Upper Confidence bounds applied to Trees) is the most commonly used tree policy in MCTS, and its core idea is to apply the UCB1 formula from multi-armed bandits to tree node selection.
50%UnverifiedUnder conditions of infinite sampling and appropriate decay of the exploration parameter, UCT-type algorithms can converge to the optimal solution of the game tree, but this conclusion relies on idealized assumptions such as the simulation policy being able to cover all actions and rewards being bounded.
50%UnverifiedPUCT 在每次选择节点时，除了利用 UCT 的探索-利用权衡项，还引入了一个基于策略网络的先验预测项，用来指导搜索往更有希望的分支扩展。
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