Maxmin and minimax are fundamental strategies in game theory. Maxmin aims to maximize the minimum payoff, ensuring a certain level of security even in unfavourable situations. Conversely, minimax aims to minimize the maximum potential loss, seeking the best possible outcome in the worst-case scenario. These strategies are particularly relevant in zero-sum games, where one player’s gain is the other’s loss. The minimax algorithm efficiently computes the best move for each player, while alpha-beta pruning optimizes the calculations.
