Search results
Results from the WOW.Com Content Network
When splitting, the R*-tree uses a topological split that chooses a split axis based on perimeter, then minimizes overlap. In addition to an improved split strategy, the R*-tree also tries to avoid splits by reinserting objects and subtrees into the tree, inspired by the concept of balancing a B-tree.
This step is sometimes also called playout or rollout. A playout may be as simple as choosing uniform random moves until the game is decided (for example in chess, the game is won, lost, or drawn). Backpropagation: Use the result of the playout to update information in the nodes on the path from C to R. Step of Monte Carlo tree search.
When data is organized in an R-tree, the neighbors within a given distance r and the k nearest neighbors (for any L p-Norm) of all points can efficiently be computed using a spatial join. [9] [10] This is beneficial for many algorithms based on such queries, for example the Local Outlier Factor.
Theorem: After O(log n) expected rake and compress steps, a tree is reduced to a single node. Now rephrase the tree contraction algorithm as follows: Input: A binary tree rooted at r; Output: A single node; Operation: A sequence of contraction steps, each consisting of a rake operation and a compress operation (in any order).
Depending on the problem at hand, pre-order, post-order, and especially one of the number of subtrees − 1 in-order operations may be optional. Also, in practice more than one of pre-order, post-order, and in-order operations may be required. For example, when inserting into a ternary tree, a pre-order operation is performed by comparing items.
The nodes of the resulting R-tree will be fully packed, with the possible exception of the last node at each level. Thus, the space utilization is ≈100%; this structure is called a packed Hilbert R-tree. The second index, called a Dynamic Hilbert R-tree, supports insertions and deletions, and is suitable for a dynamic environment.
The term prioritized arrives from the introduction of four priority-leaves that represents the most extreme values of each dimensions, included in every branch of the tree. Before answering a window-query by traversing the sub-branches, the prioritized R-tree first checks for overlap in its priority nodes. The sub-branches are traversed (and ...
A rapidly exploring random tree (RRT) is an algorithm designed to efficiently search nonconvex, high-dimensional spaces by randomly building a space-filling tree.The tree is constructed incrementally from samples drawn randomly from the search space and is inherently biased to grow towards large unsearched areas of the problem.