alphabeta

import math

def alphabeta(depth, nodeIndex, maximizingPlayer, values, alpha, beta):
    # Base case: leaf node reached
    if depth == 3:
        return values[nodeIndex]

    # Initialize bestEval based on whose turn it is
    bestEval = -math.inf if maximizingPlayer else math.inf

    # Loop through the two children (binary tree)
    for i in range(2):
        # Recursively call alphabeta. 'not maximizingPlayer' automatically toggles True to False, and False to True.
        eval = alphabeta(depth + 1, nodeIndex * 2 + i, not maximizingPlayer, values, alpha, beta)
        
        # Update the respective values based on the player
        if maximizingPlayer:
            bestEval = max(bestEval, eval)
            alpha = max(alpha, eval)
        else:
            bestEval = min(bestEval, eval)
            beta = min(beta, eval)
            
        # Alpha-beta pruning condition
        if beta <= alpha:
            break
            
    return bestEval

values = [3, 5, 6, 9, 1, 2, 0, -1]
result = alphabeta(0, 0, True, values, -math.inf, math.inf)
print("Optimal Value :", result)