简而言之，不是很好。如果你改变了《吃豆人》迷宫，眼睛就不一定会回来。有些四处游荡的黑客就有这个问题。所以它依赖于一个合作迷宫。

对于我的《吃豆人》游戏，我创造了一个“最短多条回家路径”算法，它适用于我所提供的任何迷宫(在我的规则集内)。它也适用于隧道。

当关卡被加载时，每个十字路口的所有归途数据都是空的(默认)，一旦幽灵开始探索迷宫，它们每次遇到“新的”十字路口或从不同的路径再次遇到已知的十字路口时，它们的归途路径信息就会不断更新。

简而言之，不是很好。如果你改变了《吃豆人》迷宫，眼睛就不一定会回来。有些四处游荡的黑客就有这个问题。所以它依赖于一个合作迷宫。

对于更传统的寻路算法的替代方案，您可以看看(名称很合适!)吃豆人气味反对象模式。

你可以在启动时在迷宫中弥漫怪物洞的气味，然后让眼睛跟着它回家。

气味设置好后，运行成本非常低。

编辑:很遗憾维基百科上的文章已经被删除了，所以WayBack Machine来拯救…

下面是ammoQ的洪水填充想法的模拟和伪代码。

queue q
enqueue q, ghost_origin
set visited

while q has squares
   p <= dequeue q
   for each square s adjacent to p
      if ( s not in visited ) then
         add s to visited
         s.returndirection <= direction from s to p
         enqueue q, s
      end if
   next
 next

它的思想是宽度优先搜索，所以每次你遇到一个新的相邻正方形s，最好的路径是经过p。我相信是O(N)。

最初的《吃豆人》并没有使用寻径或花哨的AI。它只是让玩家觉得游戏比实际更有深度，但实际上它是随机的。正如Ian Millington和John Funge在《ai Intelligence for Games》中所述。

Not sure if it's true or not, but it makes a lot of sense to me. Honestly, I don't see these behaviors that people are talking about. Red/Blinky for ex is not following the player at all times, as they say. Nobody seems to be consistently following the player, on purpose. The chance that they will follow you looks random to me. And it's just very tempting to see behavior in randomness, especially when the chances of getting chased are very high, with 4 enemies and very limited turning options, in a small space. At least in its initial implementation, the game was extremely simple. Check out the book, it's in one of the first chapters.