docstr: Returns the mean aggregation strategy for the multi-objective algorithm.
  
  Parameters
  ----------
  scenario : Scenario
  objective_weights : list[float] | None, defaults to None
      Weights for averaging the objectives in a weighted manner. Must be of the same length as the number of
      objectives.
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code: def get_multi_objective_algorithm(  # type: ignore
      scenario: Scenario,
      *,
      objective_weights: list[float] | None = None,
  ) -> MeanAggregationStrategy:
      """Returns the mean aggregation strategy for the multi-objective algorithm.
  
      Parameters
      ----------
      scenario : Scenario
      objective_weights : list[float] | None, defaults to None
          Weights for averaging the objectives in a weighted manner. Must be of the same length as the number of
          objectives.
      """
      return MeanAggregationStrategy(
          scenario=scenario,
          objective_weights=objective_weights,
      )
  
imports: from __future__ import annotations
  import numpy
  import sklearn.gaussian_process.kernels
  from ConfigSpace import Configuration
  from smac.acquisition.function.expected_improvement import EI
  from smac.acquisition.maximizer.local_and_random_search import LocalAndSortedRandomSearch
  from smac.facade.abstract_facade import AbstractFacade
  from smac.initial_design.sobol_design import SobolInitialDesign
  from smac.intensifier.intensifier import Intensifier
  from smac.model.gaussian_process.abstract_gaussian_process import AbstractGaussianProcess
  from smac.model.gaussian_process.gaussian_process import GaussianProcess
  from smac.model.gaussian_process.kernels import ConstantKernel, HammingKernel, MaternKernel, WhiteKernel
  from smac.model.gaussian_process.mcmc_gaussian_process import MCMCGaussianProcess
  from smac.model.gaussian_process.priors import HorseshoePrior, LogNormalPrior
  from smac.multi_objective.aggregation_strategy import MeanAggregationStrategy
  from smac.random_design.probability_design import ProbabilityRandomDesign
  from smac.runhistory.encoder.encoder import RunHistoryEncoder
  from smac.scenario import Scenario
  from smac.utils.configspace import get_types
label_desc: Use image node_id 9 for calling the BlackBoxFacade obj's underlying member method code with example usage: obj.get_multi_objective_algorithm(scenario) and returns: MeanAggregationStrategy