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Prune and search is a method of solving optimization problems suggested by Nimrod Megiddo in 1983. [1]The basic idea of the method is a recursive procedure in which at each step the input size is reduced ("pruned") by a constant factor 0 < p < 1.
In computational geometry, Megiddo is known for his prune and search and parametric search techniques both suggested in 1983 [6] [7] and used for various computational geometric optimization problems, in particular to solve the smallest-circle problem in linear time. [8] His former doctoral students include Edith Cohen. [2] [9]
Pruning is a data compression technique in machine learning and search algorithms that reduces the size of decision trees by removing sections of the tree that are non-critical and redundant to classify instances.
Alpha–beta pruning is a search algorithm that seeks to decrease the number of nodes that are evaluated by the minimax algorithm in its search tree. It is an adversarial search algorithm used commonly for machine playing of two-player combinatorial games (Tic-tac-toe, Chess, Connect 4, etc.). It stops evaluating a move when at least one ...
The following is the skeleton of a generic branch and bound algorithm for minimizing an arbitrary objective function f. [3] To obtain an actual algorithm from this, one requires a bounding function bound, that computes lower bounds of f on nodes of the search tree, as well as a problem-specific branching rule.
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An important application of divide and conquer is in optimization, [example needed] where if the search space is reduced ("pruned") by a constant factor at each step, the overall algorithm has the same asymptotic complexity as the pruning step, with the constant depending on the pruning factor (by summing the geometric series); this is known as ...
In physical simulations, sweep and prune is a broad phase algorithm used during collision detection to limit the number of pairs of solids that need to be checked for collision, i.e. intersection. This is achieved by sorting the starts (lower bound) and ends (upper bound) of the bounding volume of each solid along a number of arbitrary axes.