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YouTubeMIT OpenCourseWare
6. Search: Games, Minimax, and Alpha-Beta
MIT 6.034 Artificial Intelligence, Fall 2010 View the complete course: http://ocw.mit.edu/6-034F10 Instructor: Patrick Winston In this lecture, we consider strategies for adversarial games such as chess. We discuss the minimax algorithm, and how alpha-beta pruning improves its efficiency. We then examine progressive deepening, which ensures ...
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It is your turn to do some of the alpha-beta pruning. The tree below indicates the complete Minimax tree for a particular problem (first move by MIN, then MAX, and then MIN again – notice that is different from our previous examples, where MAX started). The number at each leaf p indicates the value of the static evaluation function e(p) if it were computed at that leaf.a) Now your job is to check the boxes under those leaves that do not need to be created and evaluated thanks to the alpha-beta p
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