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  2. Iterative deepening depth-first search - Wikipedia

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

    In computer science, iterative deepening search or more specifically iterative deepening depth-first search [1] (IDS or IDDFS) is a state space/graph search strategy in which a depth-limited version of depth-first search is run repeatedly with increasing depth limits until the goal is found.

  3. Iterative deepening A* - Wikipedia

    en.wikipedia.org/wiki/Iterative_deepening_A*

    Iterative deepening A* (IDA*) is a graph traversal and path search algorithm that can find the shortest path between a designated start node and any member of a set of goal nodes in a weighted graph. It is a variant of iterative deepening depth-first search that borrows the idea to use a heuristic function to conservatively estimate the ...

  4. A* search algorithm - Wikipedia

    en.wikipedia.org/wiki/A*_search_algorithm

    The space complexity of A* is roughly the same as that of all other graph search algorithms, as it keeps all generated nodes in memory. [1] In practice, this turns out to be the biggest drawback of the A* search, leading to the development of memory-bounded heuristic searches, such as Iterative deepening A*, memory-bounded A*, and SMA*.

  5. Depth-first search - Wikipedia

    en.wikipedia.org/wiki/Depth-first_search

    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] Another possible implementation of iterative depth-first search uses a stack of iterators of the list of neighbors of a node, instead of a stack of ...

  6. MTD(f) - Wikipedia

    en.wikipedia.org/wiki/MTD(f)

    MTD(f) is a shortened form of MTD(n,f) which stands for Memory-enhanced Test Driver with node ‘n’ and value ‘f’. [1] The efficacy of this paradigm depends on a good initial guess, and the supposition that the final minimax value lies in a narrow window around the guess (which becomes an upper/lower bound for the search from root).

  7. Monte Carlo tree search - Wikipedia

    en.wikipedia.org/wiki/Monte_Carlo_tree_search

    The rating of best Go-playing programs on the KGS server since 2007. Since 2006, all the best programs use Monte Carlo tree search. [14]In 2006, inspired by its predecessors, [15] Rémi Coulom described the application of the Monte Carlo method to game-tree search and coined the name Monte Carlo tree search, [16] L. Kocsis and Cs.

  8. Model checking - Wikipedia

    en.wikipedia.org/wiki/Model_checking

    The process can be repeated with larger and larger values of until all possible violations have been ruled out (cf. Iterative deepening depth-first search). Abstraction attempts to prove properties of a system by first simplifying it. The simplified system usually does not satisfy exactly the same properties as the original one so that a ...

  9. Graph traversal - Wikipedia

    en.wikipedia.org/wiki/Graph_traversal

    A stack (often the program's call stack via recursion) is generally used when implementing the algorithm. The algorithm begins with a chosen "root" vertex; it then iteratively transitions from the current vertex to an adjacent, unvisited vertex, until it can no longer find an unexplored vertex to transition to from its current location.