Editing Greedy algorithm (section)

==Examples==
* The [[activity selection problem]] is characteristic of this class of problems, where the goal is to pick the maximum number of activities that do not clash with each other.
* In the [[Macintosh computer]] game ''[[Crystal Quest]]'' the objective is to collect crystals, in a fashion similar to the [[travelling salesman problem]]. The game has a demo mode, where the game uses a greedy algorithm to go to every crystal. The [[artificial intelligence]] does not account for obstacles, so the demo mode often ends quickly.
* The [[matching pursuit]] is an example of a greedy algorithm applied on signal approximation.
* A greedy algorithm finds the optimal solution to [[Malfatti circles|Malfatti's problem]] of finding three disjoint circles within a given triangle that maximize the total area of the circles; it is conjectured that the same greedy algorithm is optimal for any number of circles.
* A greedy algorithm is used to construct a Huffman tree during [[Huffman coding]] where it finds an optimal solution.
* In [[decision tree learning]], greedy algorithms are commonly used, however they are not guaranteed to find the optimal solution.
**One popular such algorithm is the [[ID3 algorithm]] for decision tree construction.
*[[Dijkstra's algorithm]] and the related [[A* search algorithm]] are verifiably optimal greedy algorithms for [[graph search]] and [[Shortest path problem|shortest path finding]]. 
**A* search is conditionally optimal, requiring an "[[admissible heuristic]]" that will not overestimate path costs.
*[[Kruskal's algorithm]] and [[Prim's algorithm]] are greedy algorithms for constructing [[minimum spanning tree]]s of a given [[connected graph]]. They always find an optimal solution, which may not be unique in general.
*The [[Sequitur algorithm|Sequitur]] and [[Lempel-Ziv-Welch algorithm|Lempel-Ziv-Welch]] algorithms are [[Grammar_induction#Grammatical_inference_by_greedy_algorithms|greedy algorithms for grammar induction]].