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  2. Jump point search - Wikipedia

    en.wikipedia.org/wiki/Jump_point_search

    In computer science, jump point search (JPS) is an optimization to the A* search algorithm for uniform-cost grids. It reduces symmetries in the search procedure by means of graph pruning, [1] eliminating certain nodes in the grid based on assumptions that can be made about the current node's neighbors, as long as certain conditions relating to the grid are satisfied.

  3. Any-angle path planning - Wikipedia

    en.wikipedia.org/wiki/Any-angle_path_planning

    The advantage is that all optimizations of grid A* like jump point search will apply. A visibility graph with all the grid points can be searched with A* for the optimal solution in 2D space. However, the performance is problematic since the number of edges in a graph with V {\displaystyle V} vertices is O ( V 2 ) {\displaystyle O(V^{2})} .

  4. Isometric video game graphics - Wikipedia

    en.wikipedia.org/wiki/Isometric_video_game_graphics

    A common example is picking the tile that lies right under the cursor when a user clicks. One such method is using the same rotation matrices that originally produced the isometric view in reverse to turn a point in screen coordinates into a point that would lie on the game board surface before it was rotated. Then, the world x and y values can ...

  5. A* search algorithm - Wikipedia

    en.wikipedia.org/wiki/A*_search_algorithm

    For a grid map from a video game, using the Taxicab distance or the Chebyshev distance becomes better depending on the set of movements available (4-way or 8-way). If the heuristic h satisfies the additional condition h ( x ) ≤ d ( x , y ) + h ( y ) for every edge ( x , y ) of the graph (where d denotes the length of that edge), then h is ...

  6. Perlin noise - Wikipedia

    en.wikipedia.org/wiki/Perlin_noise

    The dot product of each point with its nearest grid node gradient value. The dot product with the other three nodes in the cell is not shown. For working out the value of any candidate point, first find the unique grid cell in which the point lies. Then, identify the 2 n corners of that cell and their associated gradient vectors. Next, for each ...

  7. Bicubic interpolation - Wikipedia

    en.wikipedia.org/wiki/Bicubic_interpolation

    Black and red / yellow / green / blue dots correspond to the interpolated point and neighbouring samples, respectively. Their heights above the ground correspond to their values. In mathematics , bicubic interpolation is an extension of cubic spline interpolation (a method of applying cubic interpolation to a data set) for interpolating data ...

  8. Maze generation algorithm - Wikipedia

    en.wikipedia.org/wiki/Maze_generation_algorithm

    Randomized depth-first search on a hexagonal grid. The depth-first search algorithm of maze generation is frequently implemented using backtracking. This can be described with a following recursive routine: Given a current cell as a parameter; Mark the current cell as visited; While the current cell has any unvisited neighbour cells

  9. Hyperparameter optimization - Wikipedia

    en.wikipedia.org/wiki/Hyperparameter_optimization

    Grid search suffers from the curse of dimensionality, but is often embarrassingly parallel because the hyperparameter settings it evaluates are typically independent of each other. [5] Random search across different combinations of values for two hyperparameters. In this example, 100 different random choices are evaluated.