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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AI
寻路
｜
201
AI
寻路
置换表
为了避免重复计算，我们可以对棋局状态计算一个散列值，并且将路径长度存储在
一个置换表中。如果该状态在后面的搜索中会被发现，而且当时深度大于已经保存
的深度，那么搜索将会终止。这种方法能够避免在一棵低效的子树中搜索。
层次化
如果棋局状态能够被分为多个层次，那么可以将搜索空间分为多个层次，以便
A
＊
搜索
算法可以在特定层运行。
层次化寻路
A*
（
HPA*
）就应用了这种方法（
Botea
等，
2004
）。
内存限制
与其限制搜索空间所需要的计算时间，我们可以执行一种“有损”搜索，在搜索的
过程中舍弃一些结点，专注于搜索那些被认为和结果相关的区域。
简化内存限制
A*
（
SMA*
）就是这样一个例子（
Russel
，
1992
）。
Reinefeld
和
Marsland
（
1994
）总结了一系列有趣的
A*
搜索
扩展算法。更多关于如
何在
AI
系统中使用
A*
搜索
的信息可以在教科书和大量的在线资源中找到（
Barr
和
Feigenbaum
，
1981
）。
7.10 比较搜索树算法
广度优先搜索
能够确保找到步数最少的解，但是它可能需要评估相当大规模的走法序列。
而
深度优先搜索
会尝试在每次搜索时能够尽可能地向前进，尽管有时候它能够非常快地
找到一个解，但是它也可能在搜索树的某个毫无希望的部分浪费大量的时间。
A*
搜索
与
一个可接受的启发式函数相结合，用最少的时间找到最优解，但要找到一个可接受的启
发式函数是非常困难的。
我们可以直接比较
深度优先搜索
、
广度优先搜索
和
A*
搜索
在求解八数码问题的表现。
我们通过随机移动
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.