The Minimax Search Algorithm is a decision-making algorithm used primarily in two-player games, such as chess or tic-tac-toe. Its purpose is to minimize the possible loss for a worst-case scenario while maximizing the potential gain. The algorithm works by constructing a game tree where each node represents a game state, and it alternates between minimizing and maximizing layers, depending on whose turn it is.
In essence, the player (maximizer) aims to choose the move that provides the maximum possible score, while the opponent (minimizer) aims to select moves that minimize the player's score. The algorithm evaluates the game states at the leaf nodes of the tree and propagates these values upward, ultimately leading to the decision that results in the optimal strategy for the player. The Minimax algorithm can be implemented recursively and often incorporates techniques such as alpha-beta pruning to enhance efficiency by eliminating branches that do not need to be evaluated.
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