问题描述
像这样:
我不知道如何为此编写代码，因为我只编写了非游戏应用程序.例如，您如何确定玩家采取行动后的最佳行动?我不需要完美的动作，只要有挑战性就行.
I am not sure how to code for this as I have only coded non-game apps. For instance how do you determine the best move after the player has made his move? I don't need the perfect moves, just challenging enough.
我不知道我是否必须扫描所有可能的动作等.在如图所示的游戏中，可能的动作数量非常有限，对吗?所以我可以把它们全部计算出来.但我不确定哪一个会更好，等等.
I don't know if I have to scan all the possible moves, etc. In a game like shown in the pic, the number of possible moves are very limited, right? So I could calculate them all. But I am not sure which one would be a better move, etc.
推荐答案
在像井字棋这样的小型简单游戏中，您可以构建一棵树，其中:
In a small, simple game like tic-tac-toe, you can build a tree, where:
- 每个节点都是一个棋盘位置
- 每个叶子节点是一个完成的游戏，+1 表示 X 获胜，-1 如果 O 获胜，0 表示平局
- 每个子节点都是其父节点合法移动的结果
然后 X 正在寻找一个可以最大化最小结果的移动，知道 O 将搜索(在他的后续回合中)一个可以最小化最大结果的移动，知道 X 将搜索(在他随后的回合中)) 的举动将...
Then X is searching for a move which will maximize the minimum result, knowing that O will search (on his subsequent turn) for a move which will minimize the maximum result, knowing that X will search (on his subsequent turn to that) for a move which will...
这是极大极小算法.
在 Tic-Tac-Toe 中，树的深度只能达到 9 层，如果您想变得光滑，可以利用一些棋盘对称性并保持计算和数据结构的可管理性.
In Tic-Tac-Toe, the tree can only get 9 layers deep, and if you want to be slick, you can take advantage of some board symmetries and keep the computations and data structures manageable.
请注意，对于更复杂的游戏，这会因某种原因而失败(国际象棋是确定性的，但太大而无法以这种方式处理；西洋双陆棋需要概率技术等)，但许多方法是这一主题的变体.
Note that for more complex games this will fail for one reason or another (chess is deterministic, but too large to handle this way; backgammon needs probabilistic techniques, etc) but many approaches are variations on this theme.
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