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  2. Depth-first search - Wikipedia

    en.wikipedia.org/wiki/Depth-first_search

    a depth-first search starting at the node A, assuming that the left edges in the shown graph are chosen before right edges, and assuming the search remembers previously visited nodes and will not repeat them (since this is a small graph), will visit the nodes in the following order: A, B, D, F, E, C, G.

  3. Iterative deepening depth-first search - Wikipedia

    en.wikipedia.org/wiki/Iterative_deepening_depth...

    function Depth-Limited-Search-Backward(u, Δ, B, F) is prepend u to B if Δ = 0 then if u in F then return u (Reached the marked node, use it as a relay node) remove the head node of B return null foreach parent of u do μ ← Depth-Limited-Search-Backward(parent, Δ − 1, B, F) if μ null then return μ remove the head node of B return null

  4. A* search algorithm - Wikipedia

    en.wikipedia.org/wiki/A*_search_algorithm

    Dijkstra's algorithm, as another example of a uniform-cost search algorithm, can be viewed as a special case of A* where ⁠ = ⁠ for all x. [12] [13] General depth-first search can be implemented using A* by considering that there is a global counter C initialized with a very large value.

  5. Search algorithm - Wikipedia

    en.wikipedia.org/wiki/Search_algorithm

    This class also includes various tree search algorithms, that view the elements as vertices of a tree, and traverse that tree in some special order. Examples of the latter include the exhaustive methods such as depth-first search and breadth-first search, as well as various heuristic-based search tree pruning methods such as backtracking and ...

  6. Iterative deepening A* - Wikipedia

    en.wikipedia.org/wiki/Iterative_deepening_A*

    It is a variant of iterative deepening depth-first search that borrows the idea to use a heuristic function to conservatively estimate the remaining cost to get to the goal from the A* search algorithm. Since it is a depth-first search algorithm, its memory usage is lower than in A*, but unlike ordinary iterative deepening search, it ...

  7. Curiously recurring template pattern - Wikipedia

    en.wikipedia.org/wiki/Curiously_recurring...

    The technique was formalized in 1989 as "F-bounded quantification."[2] The name "CRTP" was independently coined by Jim Coplien in 1995, [3] who had observed it in some of the earliest C++ template code as well as in code examples that Timothy Budd created in his multiparadigm language Leda. [4]

  8. Alpha–beta pruning - Wikipedia

    en.wikipedia.org/wiki/Alpha–beta_pruning

    In the extreme case, the search is performed with alpha and beta equal; a technique known as zero-window search, null-window search, or scout search. This is particularly useful for win/loss searches near the end of a game where the extra depth gained from the narrow window and a simple win/loss evaluation function may lead to a conclusive result.

  9. Binary search tree - Wikipedia

    en.wikipedia.org/wiki/Binary_search_tree

    Fig. 1: A binary search tree of size 9 and depth 3, with 8 at the root. In computer science, a binary search tree (BST), also called an ordered or sorted binary tree, is a rooted binary tree data structure with the key of each internal node being greater than all the keys in the respective node's left subtree and less than the ones in its right subtree.