如何code简单的AI了Windows Phone的棋盘游戏？ [英] How to code simple AI for a windows phone board game?
问题描述
事情是这样的：
我不知道如何code这个，因为我只有codeD非游戏应用程序。举例来说，你如何确定最佳的移动后的玩家提出了他的举动？我不需要完美的动作，只是足够的挑战性。
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.
我不知道有没有扫描所有可能的行动，等等。在这样的比赛中所示的知情同意，可能的移动次数是非常有限的，对不对？所以，我可以计算出他们。但我不知道哪一个会是一个更好的举措等。
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
在一个小的，简单的游戏，如井字棋，你可以建立一棵树，其中：
In a small, simple game like tic-tac-toe, you can build a tree, where:
- 在每个节点都是一个板位置
- 在每个叶子节点是+1分完成的游戏为X胜，-1如果可胜，0平局
- 在每个子节点是从它的父 法律举措的结果
- each node is a board position
- each leaf node is a finished game with a score of +1 is X wins, -1 if O wins, 0 for a draw
- each child node is the result of a legal move from its parent
则X是寻找一个此举将最大限度地最小结果，知道澳的搜索（他后来转）的举措，这将在最大结果最小化，知道X将搜索（他后来转向了）为此举将...
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。
在井字棋，树只能得到9层深，如果你想成为华而不实，您可以采取一些董事会对称性优势，保持计算和数据结构管理。
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，这将失败的原因之一或另一个（国际象棋是确定性的，但过大，以这种方式;步步高需要概率技术等），但许多方法都是这个变化的主题。
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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