When is alpha updated in the alpha-beta pruning method?

In the alpha-beta pruning method, the alpha value is specifically updated at max levels of the game tree. The alpha value represents the best score that the maximizing player (MAX) can guarantee at that point or level of the search tree. When the algorithm evaluates the children of a max node, it compares their values to the current alpha value and updates alpha only if a child node yields a higher value.

This means that during these decisions, the algorithm is actively looking to maximize the score and thus adjusts the alpha value based on the optimal outcomes that can be achieved. If a move is found that offers a better score than the previously best known score (the current alpha), that score is used for future comparisons. This updating mechanism is crucial for the effectiveness of alpha-beta pruning, as it helps cut off branches of the tree that do not require further exploration, thereby improving efficiency.

In contrast, the alpha value is not updated at minimum levels since those levels would correspond to the minimizing player (MIN) who aims to minimize the opponent's score. Similarly, while all levels are evaluated, only max levels lead to an alpha value update, and pruning does not inherently trigger an alpha update; rather, it occurs as a result of evaluating possible moves.