class_docstr: An exploration policy takes the predicted actions or action values from the agent, and selects the action to
  actually apply to the environment using some predefined algorithm.
docstr: :param action_space: the action space used by the environment
docstr_tok: [":","param","action_space",":","the","action","space","used","by","the","environment"]
code: def __init__(self, action_space: ActionSpace):
      """
      :param action_space: the action space used by the environment
      """
      self.phase = RunPhase.HEATUP
      self.action_space = action_space
  
imports: from typing import List
  from rl_coach.base_parameters import Parameters
  from rl_coach.core_types import RunPhase, ActionType
  from rl_coach.spaces import ActionSpace, DiscreteActionSpace, BoxActionSpace, GoalsSpace
label_desc: Use image node_id 1 to create a new ExplorationPolicy object from inherited base classes: object with example: obj = ExplorationPolicy(action_space)