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Now, when we talked about optimization problems in dynamic programming, I said there were two things to look for.
现在，当我们讨论,动态编程中的最优化问题时，我想说有两件事需要注意。
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And when you have an optimal substructure and the local solutions overlap, that's when you can bring dynamic programming to bear.
当你得到一个最优子结构,但局部解决方案有重跌时，你就可以引入动态编程,来解决这个问题了。
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So when you're trying to think about is this a problem that I can solve with dynamic programming, these are the two questions you ask.
所以当你想知道能否,用动态编程来解决这个问题时,你可以问自己两个问题。
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And this is what lies at the heart of this very general technique called dynamic programming.
这也就是动态编程,这种通用技术的核心。
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That's a huge improvement. And that's sort of the magic of dynamic programming.
这是一个很大的进步,这也是动态编程的魅力所在。
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In dynamic programming, one of the things that's going on is we're trading time for space.
在动态编程法中我们是在用,空间换时间，除了动态编程法。
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Dynamic programming is not the only time we do that.
我们在其他算法中也会用到这一点。
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That would let us tackle it with dynamic programming.
回答好这个问题我们,就能用动态编程法解决这个问题。
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That gets us to the smart thief. Why is this thief smart? Because she took 600. And she learned 600 that in fact there is a good way to solve this problem. And that's what we're going to talk about next. And that's something called dynamic programming.
现在我们要当聪明的贼,这个贼为什么聪明呢？,因为它选择了,它知道这事实上是解决这个问题的好方法,这就是我们接下来要讲的,也就是动态编程。
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