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  2. 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 ...

  3. Iterative deepening depth-first search - Wikipedia

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

    Iterative deepening prevents this loop and will reach the following nodes on the following depths, assuming it proceeds left-to-right as above: 0: A; 1: A, B, C, E (Iterative deepening has now seen C, when a conventional depth-first search did not.) 2: A, B, D, F, C, G, E, F (It still sees C, but that it came later.

  4. List of algorithms - Wikipedia

    en.wikipedia.org/wiki/List_of_algorithms

    Iterative deepening depth-first search (IDDFS): a state space search strategy; Jump point search: an optimization to A* which may reduce computation time by an order of magnitude using further heuristics; Lexicographic breadth-first search (also known as Lex-BFS): a linear time algorithm for ordering the vertices of a graph

  5. Depth-first search - Wikipedia

    en.wikipedia.org/wiki/Depth-first_search

    In the artificial intelligence mode of analysis, with a branching factor greater than one, iterative deepening increases the running time by only a constant factor over the case in which the correct depth limit is known due to the geometric growth of the number of nodes per level. DFS may also be used to collect a sample of graph nodes.

  6. Monte Carlo tree search - Wikipedia

    en.wikipedia.org/wiki/Monte_Carlo_tree_search

    A related method, called progressive bias, consists in adding to the UCB1 formula a element, where b i is a heuristic score of the i-th move. [ 37 ] The basic Monte Carlo tree search collects enough information to find the most promising moves only after many rounds; until then its moves are essentially random.

  7. 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*.

  8. Prim's algorithm - Wikipedia

    en.wikipedia.org/wiki/Prim's_algorithm

    As described above, the starting vertex for the algorithm will be chosen arbitrarily, because the first iteration of the main loop of the algorithm will have a set of vertices in Q that all have equal weights, and the algorithm will automatically start a new tree in F when it completes a spanning tree of each connected component of the input graph.

  9. SMA* - Wikipedia

    en.wikipedia.org/wiki/SMA*

    function simple memory bounded A *-star (problem): path queue: set of nodes, ordered by f-cost; begin queue. insert (problem. root-node); while True do begin if queue. empty then return failure; //there is no solution that fits in the given memory node:= queue. begin (); // min-f-cost-node if problem. is-goal (node) then return success; s:= next-successor (node) if! problem. is-goal (s ...

  1. Related searches iteration deepening a program is called a process known as memory transfer

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