Examples of using Depth-first in English and their translations into Hungarian
{-}
-
Colloquial
-
Official
-
Medicine
-
Ecclesiastic
-
Financial
-
Programming
-
Official/political
-
Computer
Depth-first search.
Animated example of a depth-first search.
Depth-first search.
A stack(LIFO queue) will yield a depth-first algorithm.
Depth-first search of binary tree.
The minimax algorithm performs a complete depth-first exploration of the game tree.
The depth-first search algorithm of maze generation is frequently implemented using backtracking.
Animation of generator's thinking process using Depth-First Search.
Algorithms that use depth-first search as a building block include.
There are also tree traversal algorithms that classify as neither depth-first search nor breadth-first search.
Breadth-first search Depth-first search Graph traversal Connected-component labeling Dijkstra's algorithm.
The backtracking algorithm traverses this search tree recursively,from the root down, in depth-first order.
This is not possible with a traditional depth-first search, which does not produce intermediate results.
A preordering is a list of the vertices in the order that they were first visited by the depth-first search algorithm.
Randomized algorithm similar to depth-first search used in generating a maze.
Thus, simple depth-first or breadth-first searches do not traverse every infinite tree, and are not efficient on very large trees.
Second, computer traverses F using a chosen algorithm, such as a depth-first search, coloring the path red.
To traverse any tree with depth-first search, perform the following operations recursively at each node.
They require the use of a tree structure with a root node andprovide traversal mechanisms(breadth/depth-first) that allow client programs to navigate the elements.
A convenient description of a depth-first search of a graph is in terms of a spanning tree of the vertices reached during the search.
Depth-first search is easily implemented via a stack, including recursively(via the call stack), while breadth-first search is easily implemented via a queue, including corecursively.
These searches are referred to as depth-first search(DFS), since the search tree is deepened as much as possible on each child before going to the next sibling.
Depth-first traversal of an example tree: pre-order(red): F, B, A, D, C, E, G, I, H; in-order(yellow): A, B, C, D, E, F, G, H, I; post-order(green): A, C, E, D, B, H, I, G, F.
It is a variant of iterative deepening depth-first search that borrows the idea to use a heuristic function to evaluate the remaining cost to get to the goal from the A* search algorithm.
A depth-first search ordering(not necessarily the lexicographic one), can be computed by a randomized parallel algorithm in the complexity class RNC.[11] As of 1997, it remained unknown whether a depth-first traversal could be constructed by a deterministic parallel algorithm, in the complexity class NC.[12].
Consider IDA*, which does a recursive left-to-right depth-first search from the root node, stopping the recursion once the goal has been found or the nodes have reached a maximum value ƒ.
Both the depth-first and breadth-first graph searches are adaptations of tree-based algorithms, distinguished primarily by the lack of a structurally determined"root" vertex and the addition of a data structure to record the traversal's visitation state.
Iterative deepening search(or iterative deepening depth-first search) is a general strategy, often used in combination with depth-first tree search, that finds the best depth limit.
A version of depth-first search was investigated in the 19th century by French mathematician Charles Pierre Trémaux[1] as a strategy for solving mazes.[2][3].
There are three common ways to traverse them in depth-first order: in-order, pre-order and post-order.[1] Beyond these basic traversals, various more complex or hybrid schemes are possible, such as depth-limited searches like iterative deepening depth-first search.