The rapidly random exploring tree algorithm is a Monte Carlo method that favors sampling the larger components of these structures.
The rapidly random exploring tree algorithm is a Monte Carlo method that favors sampling the larger components of these structures. Bounding volumes combined with a âmarchingâ algorithm named for these constructs is used to implement proximity queries in some collision-detection algorithms. These constructs may be used to approximate a surfaceâs medial axis, of which they can be considered a discrete analogue. Duals to these constructs can be generated by the trivial âedge flipâ algorithm. One of these constructs can be created by successive recomputation of centroids as part of Lloydâs algorithm. Non-convex polygons comprise one of these constructs when Manhattan distance is used as the norm, but in Euclidean space, these geometric constructs are constructed entirely of convex shapes and are the duals to Delaunay triangulations. For 10 points, name these eponymous diagrams that, given a set of seed points in a space, construct a tessellation by identifying the closest seed point for each point in the space.
The rapidly random exploring tree algorithm is a Monte Carlo method that favors sampling the larger components of these structures.
Voronoi diagram [or Voronoi tessellation; or Voronoi decomposition]