构建递归函数的真正数学方法如下:

1:假设你有一个函数对f(n-1)是正确的，构造f使f(n)是正确的。 2:构造f，使得f(1)是正确的。

This is how you can prove that the function is correct, mathematically, and it's called Induction. It is equivalent to have different base cases, or more complicated functions on multiple variables). It is also equivalent to imagine that f(x) is correct for all x Now for a "simple" example. Build a function that can determine if it is possible to have a coin combination of 5 cents and 7 cents to make x cents. For example, it's possible to have 17 cents by 2x5 + 1x7, but impossible to have 16 cents. Now imagine you have a function that tells you if it's possible to create x cents, as long as x < n. Call this function can_create_coins_small. It should be fairly simple to imagine how to make the function for n. Now build your function: bool can_create_coins(int n) { if (n >= 7 && can_create_coins_small(n-7)) return true; else if (n >= 5 && can_create_coins_small(n-5)) return true; else return false; } The trick here is to realize that the fact that can_create_coins works for n, means that you can substitute can_create_coins for can_create_coins_small, giving: bool can_create_coins(int n) { if (n >= 7 && can_create_coins(n-7)) return true; else if (n >= 5 && can_create_coins(n-5)) return true; else return false; } One last thing to do is to have a base case to stop infinite recursion. Note that if you are trying to create 0 cents, then that is possible by having no coins. Adding this condition gives: bool can_create_coins(int n) { if (n == 0) return true; else if (n >= 7 && can_create_coins(n-7)) return true; else if (n >= 5 && can_create_coins(n-5)) return true; else return false; } It can be proven that this function will always return, using a method called infinite descent, but that isn't necessary here. You can imagine that f(n) only calls lower values of n, and will always eventually reach 0. To use this information to solve your Tower of Hanoi problem, I think the trick is to assume you have a function to move n-1 tablets from a to b (for any a/b), trying to move n tables from a to b.

你在用哪本书?

关于算法的标准教科书是Cormen & Rivest。我的经验是，它很好地教授了递归。

递归是编程中较难掌握的部分之一，虽然它确实需要本能，但它是可以学习的。但它确实需要一个好的描述，好的例子和好的插图。

此外，30页通常是很多的，30页是用一种编程语言编写的。在你从一本普通的书中理解递归之前，不要尝试用C或Java学习递归。

这与其说是一个问题，不如说是一个抱怨。关于递归你有更具体的问题吗?就像乘法一样，人们不会写很多关于它的东西。

说到乘法，想想这个。

问题:

* b是什么?

答:

如果b = 1，就是a。 否则就是a+a*(b-1)

* (b - 1)是什么?请参考上面的问题来解决这个问题。

子函数隐式地使用递归，例如:

去迪士尼乐园自驾游

我们到了吗?(没有) 我们到了吗?(很快) 我们到了吗?(快了……) 我们到了吗? 我们到了吗?(!!!!!)

这时孩子就睡着了……

这个倒数函数是一个简单的例子:

倒计时()函数 ｛ 返回(参数[0]> 0 ? （ Console.log(参数[0])，倒计时(参数[0]- 1)): “完成” ）; ｝ 倒计时(10);

霍夫施塔特定律也适用于软件项目。

The essence of human language is, according to Chomsky, the ability of finite brains to produce what he considers to be infinite grammars. By this he means not only that there is no upper limit on what we can say, but that there is no upper limit on the number of sentences our language has, there's no upper limit on the size of any particular sentence. Chomsky has claimed that the fundamental tool that underlies all of this creativity of human language is recursion: the ability for one phrase to reoccur inside another phrase of the same type. If I say "John's brother's house", I have a noun, "house", which occurs in a noun phrase, "brother's house", and that noun phrase occurs in another noun phrase, "John's brother's house". This makes a lot of sense, and it's an interesting property of human language.

参考文献

递归与人类思想

递归

方法A调用方法A调用方法A，最终这些方法A中的一个不会调用并退出，但这是递归，因为有东西调用了它自己。

递归的例子，我想打印出硬盘驱动器上的每个文件夹名称:(在c#中)

public void PrintFolderNames(DirectoryInfo directory)
{
    Console.WriteLine(directory.Name);

    DirectoryInfo[] children = directory.GetDirectories();

    foreach(var child in children)
    {
        PrintFolderNames(child); // See we call ourself here...
    }
}

http://javabat.com是一个有趣而令人兴奋的练习递归的地方。他们的例子开始时相当简单，然后逐步扩展(如果你想这么做的话)。注意:他们的方法是在实践中学习。这是我写的一个递归函数，用来替换for循环。

for循环:

public printBar(length)
{
  String holder = "";
  for (int index = 0; i < length; i++)
  {
    holder += "*"
  }
  return holder;
}

这是做同样事情的递归。(请注意，我们重载了第一个方法，以确保它像上面那样使用)。我们还有另一种方法来维护索引(类似于上面的for语句)。递归函数必须维护自己的索引。

public String printBar(int Length) // Method, to call the recursive function
{
  printBar(length, 0);
}

public String printBar(int length, int index) //Overloaded recursive method
{
  // To get a better idea of how this works without a for loop
  // you can also replace this if/else with the for loop and
  // operationally, it should do the same thing.
  if (index >= length)
    return "";
  else
    return "*" + printBar(length, index + 1); // Make recursive call
}

简而言之，递归是一种编写更少代码的好方法。在后面的printBar中，请注意我们有一个if语句。如果我们的条件已经达到，我们将退出递归并返回到前一个方法，该方法返回到前一个方法，等等。如果我发送一个printBar(8)，我得到********。我希望通过一个简单函数的例子，它做的事情与for循环相同，这可能会有所帮助。不过，您可以在Java Bat中进行更多的练习。