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Artificial Intelligence / Game Theory

Minimax

A decision-making algorithm used in game theory and artificial intelligence to minimize the possible loss for a worst-case scenario.

Explanation

Minimax is a recursive algorithm used for choosing the next move in an n-player game, usually a two-player zero-sum game. In this strategy, one player (the maximizer) tries to achieve the highest possible score, while the opponent (the minimizer) tries to achieve the lowest possible score. The algorithm explores the game tree to determine the optimal move by assuming both players play optimally. It is widely used in games like chess, checkers, and tic-tac-toe. To improve efficiency, it is often combined with alpha-beta pruning to reduce the number of nodes evaluated in the search tree.

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