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
｜
183
AI
寻路
public interface ISearch {
Solution search(INode initial, INode goal);
}
给定一个表示初始棋局状态的结点以及一个目标结点，
ISearch
的实现将会计算出一条
路径，这条路径便是解，如果找不到解，则返回
null
。为了和博弈树相区分，这里使用
了“棋局状态”这个术语。
使用路径长度启发式信息
盲目搜索的算法不会利用当前棋局状态的信息，它仅仅是根据固定的策略来不断地深入。
深度优先
盲目搜索简单地迭代所有可行的走法，直至找到一个解法。而
广度优先
盲目搜
索将会尝试完
k
步是否能够得到可行解之后，再去尝试
k
+1
步是否能够得到。当然
，必
定存在基于当前棋局状态指导搜索的方法，对吧？
在
A*
搜索
的讨论中，我们将会给出一个如何在八数码游戏中进行搜索的例子。这个例
子使用了不同的
启发式函数
，这些启发式函数并不直接参与到游戏中来，而是会估计从
当前棋局状态到目标状态还需要多少步，然后借助这些信息指导寻路搜索。例如，在八
数码游戏中，启发式函数将会评估棋局上每个方格需要多少步才能到达它在目标棋局状
态中的位置。寻路搜索最难的地方在于如何设计一个高效的启发式函数。
7.7 深度优先搜索
深度优先搜索
试图通过不断地向前寻找可行状态来找到一条通向目标状态的路。因为某
些搜索树包含大量的棋局状态，因此
深度优先搜索
只是在最大搜索深度固定的前提下才
具有可行性。而且，搜索的过程中还必须记住哪些状态已经被访问过，以免重复访问。
深度优先搜索小结
最好情况： ...
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I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
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.