[C language] Dynamic Planning --- from entry to standing up

Dynamic programming — Entry to stand up

Dynamic programming （ English ：Dynamic programming, abbreviation DP） It's kind of in math 、 management science 、 Computer science 、 Used in economics and bioinformatics , A method of solving complex problems by decomposing the original problem into relatively simple subproblems .

Dynamic programming is often applied to problems with overlapping subproblems and optimal substructure properties , And record the results of all sub problems , Therefore, the time of dynamic programming method is often much less than that of simple solution .

Dynamic programming has two ways to solve problems: bottom-up and top-down . Top down is memory recursion , Bottom up is recursive .

The problem solved by dynamic programming has an obvious feature , Once a subproblem is solved, the result , It will not be modified in the future calculation process , This feature is called no aftereffect , The process of solving the problem forms a directed acyclic graph . Dynamic programming only solves each subproblem once , It has the function of natural pruning , So as to reduce the amount of calculation .

Common problem solving ideas

- Pruning method

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LeetCode Algorithm in practice