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.
code: def __init__(self, action_space: ActionSpace):
      # self.phase = RunPhase.HEATUP
      self.action_space = action_space
      super().__init__(action_space)
  
file_path: coach/tutorials/Resources/exploration.py
imports: import numpy
  from typing import List
  from rl_coach.core_types import ActionType
  from rl_coach.spaces import ActionSpace
  from rl_coach.exploration_policies.exploration_policy import ExplorationPolicy, ExplorationParameters
label_desc: Use image node_id 1 to create a new MyExplorationPolicy object from inherited base classes: ExplorationPolicy with example: obj = MyExplorationPolicy(action_space)