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  2. 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

  3. Depth-first search - Wikipedia

    en.wikipedia.org/wiki/Depth-first_search

    Depth-first search (DFS) is an algorithm for traversing or searching tree or graph data structures. The algorithm starts at the root node (selecting some arbitrary node as the root node in the case of a graph) and explores as far as possible along each branch before backtracking.

  4. Iterative deepening A* - Wikipedia

    en.wikipedia.org/wiki/Iterative_deepening_A*

    Iterative-deepening-A* works as follows: at each iteration, perform a depth-first search, cutting off a branch when its total cost () = + exceeds a given threshold.This threshold starts at the estimate of the cost at the initial state, and increases for each iteration of the algorithm.

  5. Dynamic programming - Wikipedia

    en.wikipedia.org/wiki/Dynamic_programming

    To do this, we use another array p[i, j]; a predecessor array. This array records the path to any square s . The predecessor of s is modeled as an offset relative to the index (in q[i, j] ) of the precomputed path cost of s .

  6. Prim's algorithm - Wikipedia

    en.wikipedia.org/wiki/Prim's_algorithm

    Different variations of the algorithm differ from each other in how the set Q is implemented: as a simple linked list or array of vertices, or as a more complicated priority queue data structure. This choice leads to differences in the time complexity of the algorithm.

  7. 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.

  8. Search algorithm - Wikipedia

    en.wikipedia.org/wiki/Search_algorithm

    Specific applications of search algorithms include: Problems in combinatorial optimization, such as: . The vehicle routing problem, a form of shortest path problem; The knapsack problem: Given a set of items, each with a weight and a value, determine the number of each item to include in a collection so that the total weight is less than or equal to a given limit and the total value is as ...

  9. Maze generation algorithm - Wikipedia

    en.wikipedia.org/wiki/Maze_generation_algorithm

    Add the walls of the cell to the wall list. While there are walls in the list: Pick a random wall from the list. If only one of the cells that the wall divides is visited, then: Make the wall a passage and mark the unvisited cell as part of the maze. Add the neighboring walls of the cell to the wall list. Remove the wall from the list.