Dynamic programming involves breaking down problems into their subproblems. By solving for the optimal subproblems and saving those results into memory to access them whenever a repeated problem needs to be solved, the algorithmic complexity decreases significantly. Implementing dynamic programming algorithms requires higher-level thinking about the problem’s patterns. To explain dynamic programming, let’s re-examine the Fibonacci sequence that was discussed in Chapter 8. Then the chapter will cover the rules of dynamic programming and walk you through some examples to make ...
© Sammie Bae 2019
Sammie BaeJavaScript Data Structures and Algorithmshttps://doi.org/10.1007/978-1-4842-3988-9_1919. Dynamic Programming
Sammie Bae1
(1)
Hamilton, ON, Canada
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