Editing Minimax (section)

=== Pseudocode ===
The [[pseudocode]] for the depth-limited minimax algorithm is given below.

 '''function''' minimax(node, depth, maximizingPlayer) '''is'''
     '''if''' depth = 0 '''or''' node is a terminal node '''then'''
         '''return''' the heuristic value of node
     '''if''' maximizingPlayer '''then'''
         value := −∞
         '''for each''' child of node '''do'''
             value := max(value, minimax(child, depth − 1, FALSE))
         '''return''' value
     '''else''' ''(* minimizing player *)''
         value := +∞
         '''for each''' child of node '''do'''
             value := min(value, minimax(child, depth − 1, TRUE))
         '''return''' value

 ''(* Initial call *)''
 minimax(origin, depth, TRUE)

The minimax function returns a heuristic value for [[leaf nodes]] (terminal nodes and nodes at the maximum search depth). Non-leaf nodes inherit their value from a descendant leaf node. The heuristic value is a score measuring the favorability of the node for the maximizing player. Hence nodes resulting in a favorable outcome, such as a win, for the maximizing player have higher scores than nodes more favorable for the minimizing player. The heuristic value for terminal (game ending) leaf nodes are scores corresponding to win, loss, or draw, for the maximizing player. For non terminal leaf nodes at the maximum search depth, an evaluation function estimates a heuristic value for the node. The quality of this estimate and the search depth determine the quality and accuracy of the final minimax result.

Minimax treats the two players (the maximizing player and the minimizing player) separately in its code. Based on the observation that <math>\ \max(a,b) = -\min(-a,-b)\ ,</math> minimax may often be simplified into the [[negamax]] algorithm.