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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172
｜
第
7
章
❶
NegMax
在每一层中都会交换玩家和对手的位置。
❷
选择子结点中的最小值（即最大负值）。
很直观地，玩家走完之后，对手肯定会试着做出最好的决定，因此，算法指导玩家选择
最好的走法，限制对手的可行走法。如果比较
Minimax
和
NegMax
的伪代码，你会看到，
这两种算法产生了两棵几乎一样的博弈树，而唯一的区别就在于它们对棋局状态的评分。
NegMax
的博弈树结构和
Minimax
的一样，因为它可以找到一样的走法，而唯一的区别
就是在
NegMax
中，原来的
Min
结点现在都是负数。试比较图
7-6
和图
7-3
，便能看到
区别所在。
图 7-6：NexMax 的博弈树
7.4.1 解决方案
注意，在例
7-3
中，每一个
MoveEvaluation
的得分是以从当前行动的选手的角度来评
估棋局状态。这样的策略能够简化算法的实现。
例
7-3
：
NegMax
实现
public class NegMaxEvaluation 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程度
*/
public NegMaxEvaluation(int ply) {
this.ply = ply;
}
public IGameMove bestMove(IGameState s, IPlayer player,
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