input: from typing import Callable, List
  
  def optimize_objective_function(func: Callable[[List[float]], float], initial_guess: List[float]) -> List[float]:
      """ Optimize the given objective function using the Nelder-Mead method.
      >>> optimize_objective_function(lambda x: sum([xi**2 for xi in x]), [0.0, 0.0, 0.0])
      [0.0, 0.0, 0.0]
      """
      from scipy.optimize import minimize
      res = minimize(func, initial_guess, method='nelder-mead', options={'xtol': 1e-8, 'disp': True})
      return res.x
output:     from scipy.optimize import minimize
      res = minimize(func, initial_guess, method='nelder-mead', options={'xtol': 1e-8, 'disp': True})
      return res.x