input: Write a function to optimize the given objective function using the minimize function from the scipy.optimize module. The function should take no arguments and return the optimized values of the variables.
  assert optimize() == [0.0, 0.0, 0.0]
  assert optimize() == [-1.0, 2.0, 0.5]
  assert optimize() == [1.0, 1.5, 1.0]
output: def optimize():
      from scipy.optimize import minimize
      def objective(x):
          return x[0]**2 + x[1]**2 + x[2]**2
      result = minimize(objective, [0, 0, 0])
      return result.x