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  2. Any-angle path planning - Wikipedia

    en.wikipedia.org/wiki/Any-angle_path_planning

    Any-angle path planning algorithms are pathfinding algorithms that search for a Euclidean shortest path between two points on a grid map while allowing the turns in the path to have any angle. The result is a path that cuts directly through open areas and has relatively few turns. [ 1 ]

  3. A* search algorithm - Wikipedia

    en.wikipedia.org/wiki/A*_search_algorithm

    The algorithm continues until a removed node (thus the node with the lowest f value out of all fringe nodes) is a goal node. [b] The f value of that goal is then also the cost of the shortest path, since h at the goal is zero in an admissible heuristic. The algorithm described so far only gives the length of the shortest path.

  4. Branch and bound - Wikipedia

    en.wikipedia.org/wiki/Branch_and_bound

    The following is the skeleton of a generic branch and bound algorithm for minimizing an arbitrary objective function f. [3] To obtain an actual algorithm from this, one requires a bounding function bound, that computes lower bounds of f on nodes of the search tree, as well as a problem-specific branching rule.

  5. File:Algorithms.pdf - Wikipedia

    en.wikipedia.org/wiki/File:Algorithms.pdf

    The LaTeX source code is attached to the PDF file (see imprint). Licensing Permission is granted to copy, distribute and/or modify this document under the terms of the GNU Free Documentation License , Version 1.2 or any later version published by the Free Software Foundation ; with no Invariant Sections, no Front-Cover Texts, and no Back-Cover ...

  6. Analysis of algorithms - Wikipedia

    en.wikipedia.org/wiki/Analysis_of_algorithms

    Since algorithms are platform-independent (i.e. a given algorithm can be implemented in an arbitrary programming language on an arbitrary computer running an arbitrary operating system), there are additional significant drawbacks to using an empirical approach to gauge the comparative performance of a given set of algorithms. Take as an example ...

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  8. 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 ...

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