class_docstr: A decision policy that chooses the action according to the agent that is currently in control.
class_docstr_tok: ["A","decision","policy","that","chooses","the","action","according","to","the","agent","that","is","currently","in","control","."]
docstr: Get the decision maker that was set by the upper level control.
docstr_tok: ["Get","the","decision","maker","that","was","set","by","the","upper","level","control","."]
code: def decision_maker(self):
      """
      Get the decision maker that was set by the upper level control.
      """
      return self._decision_maker
  
imports: import copy
  import itertools
  from enum import Enum
  from typing import Union, List, Dict
  import numpy
  from rl_coach.agents.agent_interface import AgentInterface
  from rl_coach.base_parameters import AgentParameters, VisualizationParameters
  from rl_coach.core_types import ActionInfo, EnvResponse, ActionType, RunPhase
  from rl_coach.filters.observation.observation_crop_filter import ObservationCropFilter
  from rl_coach.saver import SaverCollection
  from rl_coach.spaces import ActionSpace
  from rl_coach.spaces import AgentSelection, AttentionActionSpace, SpacesDefinition
  from rl_coach.utils import short_dynamic_import
label_desc: Use image node_id 2 for calling the SingleDecider obj's underlying member method code with example usage: obj.decision_maker() and returns: self