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  2. SMA* - Wikipedia

    en.wikipedia.org/wiki/SMA*

    SMA* or Simplified Memory Bounded A* is a shortest path algorithm based on the A* algorithm. The main advantage of SMA* is that it uses a bounded memory, while the A* algorithm might need exponential memory. All other characteristics of SMA* are inherited from A*.

  3. 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.

  4. MTD(f) - Wikipedia

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

    MTD(f) is an alpha-beta game tree search algorithm modified to use ‘zero-window’ initial search bounds, and memory (usually a transposition table) to reuse intermediate search results. MTD(f) is a shortened form of MTD(n,f) which stands for Memory-enhanced Test Driver with node ‘n’ and value ‘f’. [ 1 ]

  5. Memory-bound function - Wikipedia

    en.wikipedia.org/wiki/Memory-bound_function

    Memory bound refers to a situation in which the time to complete a given computational problem is decided primarily by the amount of free memory required to hold the working data. This is in contrast to algorithms that are compute-bound , where the number of elementary computation steps is the deciding factor.

  6. 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 ...

  7. Depth-first search - Wikipedia

    en.wikipedia.org/wiki/Depth-first_search

    Animated example of a depth-first search For the following graph: 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 ...

  8. ‘The Crossing’ by Huffington Post

    testkitchen.huffingtonpost.com/thecrossing

    Watch firsthand, in 360 video, as Susan Sarandon listens and learns about refugees' hopes, dreams and journeys

  9. Iterative deepening depth-first search - Wikipedia

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

    The edges traversed in this search form a Trémaux tree, a structure with important applications in graph theory. Performing the same search without remembering previously visited nodes results in visiting nodes in the order A, B, D, F, E, A, B, D, F, E, etc. forever, caught in the A, B, D, F, E cycle and never reaching C or G.