def alphabeta(game_state):
    """
    Find the best move for our AI agent by applying the minimax algorithm
    with alpha beta pruning.
    :param game_state: GameState object
    :return:  a tuple representing the row column of the best move
    """

    moves = game_state.possible_moves()
    best_successor = game_state.successor(moves[0], 'AI')
    best_value = abvalue(best_successor, 'user', -sys.maxsize, sys.maxsize)
    for i in range(1, len(moves)):
        successor = game_state.successor(moves[i], 'AI')
        val = abvalue(successor, 'user', -sys.maxsize, sys.maxsize)
        if val>best_value:
            best_successor = successor
            best_value = val
    return best_successor.last_move