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  2. A* search algorithm - Wikipedia

    en.wikipedia.org/wiki/A*_search_algorithm

    The A* algorithm has real-world applications. In this example, edges are railroads and h(x) is the great-circle distance (the shortest possible distance on a sphere) to the target. The algorithm is searching for a path between Washington, D.C., and Los Angeles.

  3. Anytime A* - Wikipedia

    en.wikipedia.org/wiki/Anytime_A*

    In computer science, anytime A* is a family of variants of the A* search algorithm.Like other anytime algorithms, it has a flexible time cost, can return a valid solution to a pathfinding or graph traversal problem even if it is interrupted before it ends, by generating a fast, non-optimal solution before progressively optimizing it.

  4. Lifelong Planning A* - Wikipedia

    en.wikipedia.org/wiki/Lifelong_Planning_A*

    LPA* maintains two estimates of the start distance g*(n) for each node: . g(n), the previously calculated g-value (start distance) as in A*; rhs(n), a lookahead value based on the g-values of the node's predecessors (the minimum of all g(n' ) + d(n' , n), where n' is a predecessor of n and d(x, y) is the cost of the edge connecting x and y)

  5. Pathfinding - Wikipedia

    en.wikipedia.org/wiki/Pathfinding

    A* uses this heuristic to improve on the behavior relative to Dijkstra's algorithm. When the heuristic evaluates to zero, A* is equivalent to Dijkstra's algorithm. As the heuristic estimate increases and gets closer to the true distance, A* continues to find optimal paths, but runs faster (by virtue of examining fewer nodes).

  6. Any-angle path planning - Wikipedia

    en.wikipedia.org/wiki/Any-angle_path_planning

    There are also A*-based algorithm distinct from the above family: The performance of a visibility graph approach can be greatly improved by a sparse approach that only considers edges able to form taut paths. A multi-level version called ENLSVG is known to be faster than ANYA, but it can only be used with pre-processing. [19]

  7. Search algorithm - Wikipedia

    en.wikipedia.org/wiki/Search_algorithm

    In computer science, a search algorithm is an algorithm designed to solve a search problem. Search algorithms work to retrieve information stored within particular data structure , or calculated in the search space of a problem domain, with either discrete or continuous values .

  8. Admissible heuristic - Wikipedia

    en.wikipedia.org/wiki/Admissible_heuristic

    The search algorithm uses the admissible heuristic to find an estimated optimal path to the goal state from the current node. For example, in A* search the evaluation function (where is the current node) is: = + where = the evaluation function.

  9. List of algorithms - Wikipedia

    en.wikipedia.org/wiki/List_of_algorithms

    An algorithm is fundamentally a set of rules or defined procedures that is typically designed and used to solve a specific problem or a broad set of problems.. Broadly, algorithms define process(es), sets of rules, or methodologies that are to be followed in calculations, data processing, data mining, pattern recognition, automated reasoning or other problem-solving operations.