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dynamic programming

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Markhor answered on May 31, 2022 Popularity 10/10 Helpfulness 2/10

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Dynamic programming is used where we have problems, 
which can be divided into similar sub-problems, 
so that their results can be re-used.

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Source: www.tutorialspoint.com

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Contributed on May 31 2022

Markhor

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//_divide & conquer + memoization == top-down dynamic programming
Well, recursion+memoization is precisely a specific "flavor" of dynamic programming: dynamic programming in accordance with top-down approach.
More precisely, there's no requrement to use recursion specifically. Any divide & conquer solution combined with memoization is top-down dynamic programming. (Recursion is LIFO flavor of divide & conquer, while you can also use FIFO divide & conquer or any other kind of divide & conquer).

So it is more correct to say that
divide & conquer + memoization == top-down dynamic programming

Also, from a very formal point of view, if you implement a divide & conquer solution for a problem that does not generate repetitive partial solutions (meaning that there's no benefit in memoization), then you can claim that this divide & conquer solution is a degenerate example of "dynamic programming".
However, dynamic programming is a more general concept. Dynamic programming can use bottom-up approach, which is different from divide & conquer+memoization.

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Contributed on Jun 28 2022

Hilarious Hummingbird

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what is dynamic programming

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Dynamic programming amounts to breaking down an optimization problem into simpler sub-problems, 
and storing the solution to each sub-problem so that each sub-problem is only solved once.

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Source: www.freecodecamp.org

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Contributed on Sep 02 2022

Mahdi Jafari

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