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Looks like alpha beta with a good evaluation function, move ordering, and a changing depth parameter (not sure about this one, though).

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Isn't alpha-beta pruning a type of optimization you can do to a search algorithm, but not the base algorithm itself? I only bring this up since I helped make an Othello bot that used Mini-max _with_ alpha-beta pruning to help reduce the number of branches it needed to follow down a tree.

Alpha-Beta pruning is, to my knowledge, only really defined in a mini-max setup. By definition, it leverages the mini-max framework to prune areas of the search space.

You can apply the core concept -- refusing to expend computation effort when the result of that effort is guaranteed to not be used -- to any number of other methods and approaches in Machine Learning and AI.

As far as the first line in the wikipedia page goes..."Alpha-beta pruning is a search algorithm which seeks to reduce the number of nodes that are evaluated by the minimax algorithm in its search tree."[1] it seems like you're correct. Thanks.

[1] http://en.wikipedia.org/wiki/Alpha-beta_pruning

Ah, thanks. Nothing that couldn't be implemented in a number of languages, then...

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