Statements (53)
| Predicate | Object |
|---|---|
| gptkbp:instance_of |
gptkb:Artificial_Intelligence
|
| gptkbp:bfsLayer |
4
|
| gptkbp:bfsParent |
gptkb:What_So_Not
|
| gptkbp:applies_to |
problem solving
|
| gptkbp:benefits |
modularity
scalability improves efficiency ease of implementation reduces complexity not suitable for all problems overhead of recursion requires additional memory |
| gptkbp:characteristics |
recursive algorithms
|
| gptkbp:example |
merge sort
binary search quick sort |
| gptkbp:historical_significance |
developed in the 1960s
|
| https://www.w3.org/2000/01/rdf-schema#label |
Divide & Conquer
|
| gptkbp:influenced_by |
gptkb:Robert_Sedgewick
gptkb:John_von_Neumann gptkb:Donald_Knuth |
| gptkbp:related_to |
dynamic programming
greedy algorithms divide-and-conquer algorithms divide-and-conquer analysis divide-and-conquer applications divide-and-conquer approach divide-and-conquer frameworks divide-and-conquer methods divide-and-conquer paradigm divide-and-conquer performance divide-and-conquer principles divide-and-conquer problems divide-and-conquer recurrence relations divide-and-conquer solutions divide-and-conquer strategies divide-and-conquer strategy divide-and-conquer techniques divide-and-conquer theorem |
| gptkbp:used_in |
gptkb:computer_science
gptkb:search_algorithms gptkb:software_framework image processing algorithm design data processing database management parallel computing optimization problems network routing graphics rendering sorting algorithms computational geometry numerical algorithms |