August 2017
Intermediate to advanced
360 pages
8h 35m
Chinese
Content preview from 算法技术手册（原书第2 版）
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178
｜
第
7
章
当失去有利时机时，搜索将会剪掉那些确定会失败的子树，即
α
≥
β
的情况。如果
AlphaBeta
基于
Minimax
，那么存在两种剪枝的方法，即
α
剪枝和
β
剪枝，而当
AlphaBeta
基于
NegMax
时，只有一种剪枝的方法。因为
AlphaBeta
是递归的，那
么
[
α
,
β
]
表示玩家的获胜机会大小，
[
－
β
,
－
α
]
表示对手获胜机会的大小。在递归调用
AlphaBeta
时，会轮流从玩家和对手的角度来考虑问题，则这个获胜机会的范围也会随
之改变。
7.5.1 解决方案
例
7-4
的
AlphaBeta
实现基于
NegMax
。如果在当前棋局状态下，玩家不能保证一个更
好的位置（
α
剪枝）或者对手不能强迫玩家走到一个更坏的位置（
β
剪枝），那么搜索终止。
例
7-4
：
AlphaBeta
实现
public class AlphaBetaEvaluation implements IEvaluation {
IGameState state; /**
在搜索中将会修改的状态。
*/
int ply; /**
分支数深度，决定搜索进行到什么深度
*/
public AlphaBetaEvaluation(int ply) { this.ply = ply; }
public IGameMove bestMove(IGameState s,
IPlayer player, IPlayer opponent) {
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