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  2. Probabilistic roadmap - Wikipedia

    en.wikipedia.org/wiki/Probabilistic_roadmap

    The probabilistic roadmap [1] planner is a motion planning algorithm in robotics, which solves the problem of determining a path between a starting configuration of the robot and a goal configuration while avoiding collisions. An example of a probabilistic random map algorithm exploring feasible paths around a number of polygonal obstacles

  3. A* search algorithm - Wikipedia

    en.wikipedia.org/wiki/A*_search_algorithm

    A* is an informed search algorithm, or a best-first search, meaning that it is formulated in terms of weighted graphs: starting from a specific starting node of a graph, it aims to find a path to the given goal node having the smallest cost (least distance travelled, shortest time, etc.).

  4. Bidirectional search - Wikipedia

    en.wikipedia.org/wiki/Bidirectional_search

    Bidirectional search is a graph search algorithm that finds a shortest path from an initial vertex to a goal vertex in a directed graph. It runs two simultaneous searches: one forward from the initial state, and one backward from the goal, stopping when the two meet.

  5. Greedy algorithm - Wikipedia

    en.wikipedia.org/wiki/Greedy_algorithm

    For example, a greedy strategy for the travelling salesman problem (which is of high computational complexity) is the following heuristic: "At each step of the journey, visit the nearest unvisited city." This heuristic does not intend to find the best solution, but it terminates in a reasonable number of steps; finding an optimal solution to ...

  6. Viterbi algorithm - Wikipedia

    en.wikipedia.org/wiki/Viterbi_algorithm

    Viterbi path and Viterbi algorithm have become standard terms for the application of dynamic programming algorithms to maximization problems involving probabilities. [3] For example, in statistical parsing a dynamic programming algorithm can be used to discover the single most likely context-free derivation (parse) of a string, which is ...

  7. Breadth-first search - Wikipedia

    en.wikipedia.org/wiki/Breadth-first_search

    Breadth-first search can be used to solve many problems in graph theory, for example: Copying garbage collection, Cheney's algorithm; Finding the shortest path between two nodes u and v, with path length measured by number of edges (an advantage over depth-first search) [14] (Reverse) Cuthill–McKee mesh numbering

  8. Visibility graph - Wikipedia

    en.wikipedia.org/wiki/Visibility_graph

    Visibility graphs may be used to find Euclidean shortest paths among a set of polygonal obstacles in the plane: the shortest path between two obstacles follows straight line segments except at the vertices of the obstacles, where it may turn, so the Euclidean shortest path is the shortest path in a visibility graph that has as its nodes the start and destination points and the vertices of the ...

  9. Random walk - Wikipedia

    en.wikipedia.org/wiki/Random_walk

    An elementary example of a random walk is the random walk on the integer number line which starts at 0, and at each step moves +1 or −1 with equal probability. Other examples include the path traced by a molecule as it travels in a liquid or a gas (see Brownian motion ), the search path of a foraging animal, or the price of a fluctuating ...