kd-tree
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In computer science, a kd-tree (short for k-dimensional tree) is a space-partitioning data structure for organizing points in a k-dimensional space. kd-trees are a useful data structure for several applications, such as searches involving a multidimensional search key (e.g. range searches and nearest neighbour searches). kd-trees are a special case of BSP trees.
In Robocode, a kd-tree is a data structure use for k-nearest neighbours searching in Dynamic Clustering data logging algorithms. Currently, the most popular type of kd-tree in Robocode is the Bucket PR kd-tree.
How it works?
Please complete this section if you can (about real kd-tree, not bucket PR kd-tree)
Bucket PR kd-tree
Please complete this section if you can
Implementations
There are several implementation of kd-tree around today, and most if not all of them are bucket PR kd-trees:
- Rednaxela's kd-tree: The fastest and most efficient kd-tree around today.
- Voidious's kd-tree: The second-to-top tree.
- Simonton's kd-tree: The first bucket PR kd-tree in Robocode community.
