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  2. Best-first search - Wikipedia

    en.wikipedia.org/wiki/Best-first_search

    Best-first search is a class of search algorithms which explores a graph by expanding the most promising node chosen according to a specified rule.. Judea Pearl described best-first search as estimating the promise of node n by a "heuristic evaluation function () which, in general, may depend on the description of n, the description of the goal, the information gathered by the search up to ...

  3. Tree traversal - Wikipedia

    en.wikipedia.org/wiki/Tree_traversal

    In depth-first search (DFS), the search tree is deepened as much as possible before going to the next sibling. To traverse binary trees with depth-first search, perform the following operations at each node: [3] [4] If the current node is empty then return. Execute the following three operations in a certain order: [5] N: Visit the current node.

  4. Breadth-first search - Wikipedia

    en.wikipedia.org/wiki/Breadth-first_search

    If G is a tree, replacing the queue of this breadth-first search algorithm with a stack will yield a depth-first search algorithm. For general graphs, replacing the stack of the iterative depth-first search implementation with a queue would also produce a breadth-first search algorithm, although a somewhat nonstandard one. [10]

  5. Depth-first search - Wikipedia

    en.wikipedia.org/wiki/Depth-first_search

    If G is a tree, replacing the queue of the breadth-first search algorithm with a stack will yield a depth-first search algorithm. For general graphs, replacing the stack of the iterative depth-first search implementation with a queue would also produce a breadth-first search algorithm, although a somewhat nonstandard one. [7]

  6. Biconnected component - Wikipedia

    en.wikipedia.org/wiki/Biconnected_component

    The depth is standard to maintain during a depth-first search. The lowpoint of v can be computed after visiting all descendants of v (i.e., just before v gets popped off the depth-first-search stack ) as the minimum of the depth of v , the depth of all neighbors of v (other than the parent of v in the depth-first-search tree) and the lowpoint ...

  7. Talk:Breadth-first search - Wikipedia

    en.wikipedia.org/wiki/Talk:Breadth-first_search

    The line just below the Breadth-first search explanation. It uses the opposite strategy as depth-first search, which instead explores the highest-depth nodes first before being forced to backtrack and expand shallower nodes. This is incorrect. The algorithm does not know about highest-depth or shallow-depth nodes.

  8. Parallel breadth-first search - Wikipedia

    en.wikipedia.org/wiki/Parallel_breadth-first_search

    The breadth-first-search algorithm is a way to explore the vertices of a graph layer by layer. It is a basic algorithm in graph theory which can be used as a part of other graph algorithms. For instance, BFS is used by Dinic's algorithm to find maximum flow in a graph.

  9. Talk:Depth-first search - Wikipedia

    en.wikipedia.org/wiki/Talk:Depth-first_search

    For breadth-first search it doesn't affect the correctness of the algorithm whether you do the check before enqueueing or after dequeueing. But for depth-first search, it does matter. The paragraph below the part you quoted tries to point this out, maybe somewhat unclearly. It could be improved, perhaps.