11/11/2022 0 Comments Alpha beta![]() ![]() ![]() Now E looks at its left child which is 6.At E the values of alpha and beta is not -INF and +INF but instead -INF and 5 respectively, because the value of beta was changed at B and that is what B passed down to E.B now calls E to see if he can get a lower value than 5. The minimizer is now guaranteed a value of 5 or lesser. D now looks at its right child which returns a value of 5.At D, alpha = max(3, 5) which is 5.This is false since beta = +INF and alpha = 3. To decide whether its worth looking at its right node or not, it checks the condition betaNow the value of alpha at D is max( -INF, 3) which is 3. At D, it looks at its left child which is a leaf node.At B it the minimizer must choose min of D and E and hence calls D first.At A the maximizer must choose max of B and C, so A calls B first These values are passed down to subsequent nodes in the tree. The value of alpha here is -INFINITY and the value of beta is +INFINITY. Value = minimax(node, depth+1, true, alpha, beta) 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. K maximum sum combinations from two arrays.Minimum product of k integers in an array of positive Integers.Median of Stream of Running Integers using STL.Median in a stream of integers (running integers). ![]() Longest Increasing Subsequence Size (N log N).Maximum size square sub-matrix with all 1s.Maximum size rectangle binary sub-matrix with all 1s.Top 20 Dynamic Programming Interview Questions.Game of N stones where each player can remove 1, 3 or 4.Find the winner of the game with N piles of boxes.Minimax Algorithm in Game Theory | Set 5 (Zobrist Hashing).Minimax Algorithm in Game Theory | Set 4 (Alpha-Beta Pruning).Minimax Algorithm in Game Theory | Set 3 (Tic-Tac-Toe AI – Finding optimal move).Minimax Algorithm in Game Theory | Set 1 (Introduction).Combinatorial Game Theory | Set 4 (Sprague – Grundy Theorem).Combinatorial Game Theory | Set 3 (Grundy Numbers/Numbers and Mex).Combinatorial Game Theory | Set 1 (Introduction).Combinatorial Game Theory | Set 2 (Game of Nim).ISRO CS Syllabus for Scientist/Engineer Exam.ISRO CS Original Papers and Official Keys.GATE CS Original Papers and Official Keys. ![]()
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