Alpha-Beta pruning
Minimax search is an efficient strategy, but it still ends up exploring parts of the tree that are irrelevant. Let's consider a tree where we are supposed to search for solutions. Once we find an indicator on a node that tells us that the solution does not exist in that sub-tree, there is no need to evaluate that sub-tree. But Minimax search is a bit too conservative, so it ends up exploring that sub-tree.
We need to be smart about it and avoid searching a part of a tree that is not necessary. This process is called pruning and Alpha-Beta pruning is a type of avoidance strategy that is used to avoid searching parts of the tree that do not contain the solution.
The Alpha and Beta parameters in alpha-beta pruning refer to the two ...
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