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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.).
The pruning algorithm is a technique used in digital image processing based on mathematical morphology. [1] It is used as a complement to the skeleton and thinning algorithms to remove unwanted parasitic components (spurs).
Pruning processes can be divided into two types (pre- and post-pruning). Pre-pruning procedures prevent a complete induction of the training set by replacing a stop criterion in the induction algorithm (e.g. max. Tree depth or information gain (Attr)> minGain).
For example, if there's a bad frost, it will damage the ends of the branches first. ... "Lightly prune them in early spring, and avoid any heavy cutting, while focusing on shaping over doing any ...
For example, diverting a footpath around a tree's drip line so the crown lift is not needed. Another solution would be to prop up or cable-brace the low hanging branch. This is a non-invasive solution which in some situations may be more economical and environmentally friendly.
Bruce Ballard was the first to develop a technique, called *-minimax, that enables alpha-beta pruning in expectiminimax trees. [3] [4] The problem with integrating alpha-beta pruning into the expectiminimax algorithm is that the scores of a chance node's children may exceed the alpha or beta bound of its parent, even if the weighted value of each child does not.
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 .
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