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1. Dictionary

   Divide and conquer

   • ▪ the policy of maintaining control over one's subordinates or opponents by encouraging dissent between them, thereby preventing them from uniting in opposition

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2. Top results related to define divide and conquer

   • divide and conquer and recursion

     Top Answer

     Answered Feb 12, 2010 · 26 votes

     "Always" is a scary word, but I can't think of a divide-and-conquer situation in which you couldn't use recursion. It is by definition that divide-and-conquer creates subproblems of the same form as the initial problem - these subproblems are continually broken down until some base case is reached, and the number of divisions correlates with the size of the input. Recursion is a natural choice for this kind of problem.

     See the Wikipedia article for more good information.

     Other Answers

     Answered Feb 12, 2010 · 8 votes

     A Divide-and-conquer algorithm is by definition one that can be solved by recursion. So the answer is yes.

     Other Answers

     Answered Feb 12, 2010 · 1 votes

     Usually, yes! Merge sort is an example of the same. Here is an animated version of the same.

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     1/5

   • Divide and conquer paradigm and recursion in C - Merge sort example

     Top Answer

     Answered Jul 04, 2013 · 2 votes

     I am not sure why you are asking people to make you understand the algorithm. I can just assist you you but you have to go through it.

     In merge short you have to cut the array in two pieces. suppose you have 10 elements then high=0 and low=10-1=1. mid = (9+0)/2 = 4. So, you have divided the main array to 2 parts from 1th element to 5th and from 6th element to 10th (1..10). When ever you have more than one element in a piece you cut it into two again. At the end merge them i.e. add arrays again but in ascending order. Finally you get a single array sorted. Its very tough to explain every piece. I think this link from wiki can help. http://en.wikipedia.org/wiki/Merge_sort

     Now comes the function calling. main function is calling merge_sort it will pass low and hight (the full range of array) but within this function the merge_sort will be called by himself twice with first half range (starting to mid way and after midway to last element). Each call will again do the same (divide the array and call with first half and send half). This process will go on. merge function will add the array in sorted manner. Thats all you need. If you are not clear print or debug the value of parameters.

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     2/5

   • Divide and conquer, dynamic programming and greedy algorithms!

     Top Answer

     Answered Nov 23, 2016 · 8 votes

     When I have a problem with optimal substructur and no subproblem shares subsubproblems then I can use a divide and conquer algorithm to solve it?

     Yes, as long as you can find an optimal algorithm for each kind of subproblem.

     But when the subproblem shares subsubproblems (overlapping subproblems) then I can use dynamic programming to solve the problem?

     Is this correct?

     Yes. Dynamic programming is basically a special case of the family of Divide & Conquer algorithms, where all subproblems are the same.

     And how is greedy algorithms similar to dynamic programming?

     They're different. Dynamic programming gives you the optimal solution. A Greedy algorithm usually give a good/fair solution in a small amount of time but it doesn't assure to reach the optimum.

     It is, let's say, similar because it usually divides the solution construction in several stages in which it takes choices that are locally optimal. But if stages are not optimal substructures of the original problem, then normally it doesn't lead to the best solution.

     EDIT:

     As pointed out by @rrenaud, there are some greedy algorithms that have been proven to be optimal (e.g. Dijkstra, Kruskal, Prim etc.). So, to be more correct, the main difference between greedy and dynamic programming is that the former is not exhaustive on the space of solutions while the latter is. In fact greedy algorithms are short-sighted on that space, and each choice made during solution construction is never reconsidered.

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     3/5

   • Divide and Conquer - Easy Articles

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     4/5

   • Divide and conquer strategy python

     Top Answer

     Answered Apr 26, 2020 · 1 votes

     This is my python version code for the algorithm in its "closest larger right" version. Obviously, as you can see it is recursive. Recursion is really elegant but a bit tricky because few lines of code condense lots of concepts regarding to algorithms design and the own language they are coded. In my opinion 4 relevant moments are happening:

     • 1) Recursive calls. Function is call to itself. During this step the list progresible slice into halves. Once the atomic unit is reached the base algorithm will be executed over them firstly (step 3). if not solution is reached greater list sizes will be involved in the calculation in further recursions.
     • 2) Termination condition. Previous step is not run forever, it allows stop recursion and going to the next step (base algorithm). Now the code has len(arr) > 1: that means that the atomic unit will be pairs of numbers (or one of three in case of odd list). You can increase the number so that the recursive function will stay less time slicing the list and summarizing the results, but the counterpart is that in a parallelized environment "workers" will have to digest a bigger list.
     • 3) Base algorithm. It makes the essential calculation. Whatever the size of the list, it returns the indexes of its elements to the right closest larger number
     • 4) "Calculation saving". The base algorithm no need to calculated indexes on those numbers resolved in previous recursions. There is also a break to stop calculations once the number gets the index in the current recursion list.

     Other algorithms models could be design, more efficient for sure. It occurs to me ones based on dictionaries or on different slicing strategies.

     def closest_larger_right(arr):- len_total = len(arr) result = [None] * len_total- def recursive(arr, len_total, position=0):- # 2) Termination condition if len(arr) > 1:- mid = len(arr) // 2 left = arr[:mid] right = arr[mid:]- position_left = 0 + position position_right = len(left) + position- # 1) Recursive calls recursive(left, len_total, position_left) recursive(right, len_total, position_right)- # 3) Base algorithm for i in range(len(arr)-1): # 4) Calculation saving if result[i + position] is None: for j in range(i+1, len(arr), 1): if (arr[i] < arr[j]): result[i + position] = j + position break return result- return recursive(arr, len_total)-# output: [2, 2, 3, 7, 5, 7, 7, None]print(closest_larger_right([5, 2, 6, 8, 1, 4, 3, 9]))--

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3. People also ask

   What is divide and conquer?

   • Divide and conquer is a way to break complex problems into smaller problems that are easier to solve, and then combine the answers to solve the original problem.

   Divide and Conquer | Brilliant Math & Science Wiki

   brilliant.org/wiki/divide-and-conquer/

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   What is a divide and conquer algorithm?

   • Divide and conquer is a powerful algorithm design technique used to solve many important problems such as mergesort, quicksort, calculating Fibonacci numbers, and performing matrix multiplication. There are also many problems that humans naturally use divide and conquer approaches to solve, such as …

   Divide and Conquer | Brilliant Math & Science Wiki

   brilliant.org/wiki/divide-and-conquer/

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   How do you solve a problem using divide and conquer?

   • The main steps are: Divide: Break the problem into smaller subproblems. Conquer: Solve the subproblems recursively. Combine: Merge or combine the solutions of the subproblems to obtain the solution to the original problem. 3. What are some examples of problems solved using Divide and Conquer?

   Introduction to Divide and Conquer Algorithm - GeeksforGeeks

   www.geeksforgeeks.org/introduction-to-divide-and-conquer-algorithm-data-structure-and-algorithm-tutorials/

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   Does divide and conquer have a recursive step?

   • Divide and conquer has a recursive step, where subproblems are solved, and a base case, which is the point where the problem can't be broken down any further. How do you order a deck of cards?

   Divide and Conquer | Brilliant Math & Science Wiki

   brilliant.org/wiki/divide-and-conquer/

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4. www.merriam-webster.com › dictionary › divide andDivide and conquer Definition & Meaning - Merriam-Webster

   www.merriam-webster.com › dictionary › divide and

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   Apr 10, 2024 · The meaning of DIVIDE AND CONQUER is to make a group of people disagree and fight with one another so that they will not join together against one. How to use divide and conquer in a sentence.

5. dictionary.cambridge.org › divide-and-conquerDIVIDE AND CONQUER | English meaning - Cambridge Dictionary

   dictionary.cambridge.org › divide-and-conquer

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   DIVIDE AND CONQUER definition: a way of keeping yourself in a position of power by causing disagreements among other people so…. Learn more.

6. www.geeksforgeeks.org › divide-and-conquerDivide and Conquer Algorithm - GeeksforGeeks

   www.geeksforgeeks.org › divide-and-conquer

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   • What Is Divide and Conquer?
   • Applications of Divide and Conquer
   • Basics of Divide and Conquer
   • Standard Algorithms on Divide and Conquer
   • Binary Search Based Problems
   • Practice Problems on Divide and Conquer

   Divide and Conquer is a problem-solving technique that involves breaking a larger problem into subproblems, solving the subproblems independently and combining the solutions of those subproblems to get the solution of the larger problem.

   See full list on geeksforgeeks.org

   Merge Sort: Merge sort is a classic example of a divide and conquer sorting algorithm. It breaks down the array into smaller subarrays, sorts them individually, and then merges them to obtain the s...

   Median Finding:The median of a set of numbers can be found using a divide and conquer approach. By recursively dividing the set into smaller subsets, the median can be determined efficiently.

   Min and Max finding:Divide and Conquer algorithm can be used to find both the minimum and maximum elements in an array simultaneously. By splitting the array into halves and comparing the min-max p...

   Matrix Multiplication: Strassen’s algorithm for matrix multiplication is a divide and conquer technique that reduces the number of multiplications required for large matrices by breaking down the m...

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   Introduction to Divide and Conquer

   Dynamic Programming vs Divide-and-Conquer

   Decrease and Conquer

   Advanced master theorem for divide and conquer recurrences

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   Binary Search

   Merge Sort

   Quick Sort

   Calculate pow(x, n)

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   Find a peak element in a given array

   Check for Majority Element in a sorted array

   K-th Element of Two Sorted Arrays

   Find the number of zeroes

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   Square root of an integer

   Maximum and minimum of an array using minimum number of comparisons

   Find frequency of each element in a limited range array in less than O(n) time

   Tiling Problem

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7. Videos

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8. www.dictionary.com › browse › divide-and-conquerDIVIDE AND CONQUER Definition & Meaning | Dictionary.com

   www.dictionary.com › browse › divide-and-conquer

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   Divide and conquer definition: . See examples of DIVIDE AND CONQUER used in a sentence.

9. www.geeksforgeeks.org › introduction-to-divide-andIntroduction to Divide and Conquer Algorithm - GeeksforGeeks

   www.geeksforgeeks.org › introduction-to-divide-and

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   May 1, 2024 · Divide and Conquer Algorithm Definition: Divide and Conquer Algorithm involves breaking a larger problem into smaller subproblems, solving them independently, and then combining their solutions to solve the original problem. The basic idea is to recursively divide the problem into smaller subproblems until they become simple enough to be solved ...

10. brilliant.org › wiki › divide-and-conquerDivide and Conquer | Brilliant Math & Science Wiki

    brilliant.org › wiki › divide-and-conquer

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    Divide and conquer is a way to break complex problems into smaller problems that are easier to solve, and then combine the answers to solve the original problem. Divide and conquer is a powerful algorithm design technique used to solve many important problems such as mergesort, quicksort, calculating Fibonacci numbers, and performing matrix multiplication. There are also many problems that ...

11. www.freecodecamp.org › news › divide-and-conquerDivide and Conquer Algorithm Meaning: Explained with Examples

    www.freecodecamp.org › news › divide-and-conquer

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    Nov 26, 2019 · The Divide and Conquer algorithm solves the problem in O(nLogn) time. Strassen’s Algorithm is an efficient algorithm to multiply two matrices. A simple method to multiply two matrices need 3 nested loops and is O(n^3). Strassen’s algorithm multiplies two matrices in O(n^2.8974) time. Cooley–Tukey Fast Fourier Transform (FFT) algorithm is ...