(Recall: In alphabeta search, at each MAX node, alpha tracks the best (so, maximum) score so far that MAX can get. Similarly, at each MIN node beta tracks the best (so, minimum) score so far that MIN can get.) Assume that x is a MIN node with current beta value B obtained by picking a child y of x. Assume that minimax search now starts at child z of x, so a MAX node. If at z the alpha value a grows so that a > B then we can stop searching at z, since MIN can always prefer child y (with value 3) to child z (with value > a > B). ( fill in the blanks) Assume that x is a MAX node with current alpha value a obtained by picking a child y of x. Assume that minimax search now starts at child z of x, so a node. If at z the beta value 3 drops so that B < a then we can stop searching at z, since

Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
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(Recall: In alphabeta search, at each MAX node, alpha tracks the best (so, maximum) score
so far that MAX can get. Similarly, at each MIN node beta tracks the best (so, minimum)
score so far that MIN can get.)
Assume that x is a MIN node with current beta value 3 obtained by picking a child
of x.
Assume that minimax search now starts at child z of x, so a MAX node. If at z the alpha
value a grows so that a > ß then we can stop searching at z, since MIN can always prefer
child y (with value 3) to child z (with value > a > B).
( fill in the blanks) Assume that x is a MAX node with current alpha value a obtained by
picking a child y of x. Assume that minimax search now starts at child z of x, so a
node. If at z the beta value B drops so that B< a then we can stop searching at z, since
Transcribed Image Text:(Recall: In alphabeta search, at each MAX node, alpha tracks the best (so, maximum) score so far that MAX can get. Similarly, at each MIN node beta tracks the best (so, minimum) score so far that MIN can get.) Assume that x is a MIN node with current beta value 3 obtained by picking a child of x. Assume that minimax search now starts at child z of x, so a MAX node. If at z the alpha value a grows so that a > ß then we can stop searching at z, since MIN can always prefer child y (with value 3) to child z (with value > a > B). ( fill in the blanks) Assume that x is a MAX node with current alpha value a obtained by picking a child y of x. Assume that minimax search now starts at child z of x, so a node. If at z the beta value B drops so that B< a then we can stop searching at z, since
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