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Value = minimax(node, depth+1, false, alpha, beta) Pseudocode : function minimax(node, depth, isMaximizingPlayer, alpha, beta): Let’s define the parameters alpha and beta.Īlpha is the best value that the maximizer currently can guarantee at that level or above.īeta is the best value that the minimizer currently can guarantee at that level or above. It is called Alpha-Beta pruning because it passes 2 extra parameters in the minimax function, namely alpha and beta. It cuts off branches in the game tree which need not be searched because there already exists a better move available. This allows us to search much faster and even go into deeper levels in the game tree. It reduces the computation time by a huge factor. Prerequisites: Minimax Algorithm in Game Theory, Evaluation Function in Game TheoryĪlpha-Beta pruning is not actually a new algorithm, rather an optimization technique for minimax algorithm.
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Median of Stream of Running Integers using STL.
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