docstr: Get a decision of the next action to take.
  The action is dependent on the current state which the agent holds from resetting the environment or from
  the observe function.
  :return: A tuple containing the actual action and additional info on the action
docstr_tok: ["Get","a","decision","of","the","next","action","to","take",".","The","action","is","dependent","on","the","current","state","which","the","agent","holds","from","resetting","the","environment","or","from","the","observe","function",".",":","return",":","A","tuple","containing","the","actual","action","and","additional","info","on","the","action"]
code: def act(self) -> ActionInfo:
      """
      Get a decision of the next action to take.
      The action is dependent on the current state which the agent holds from resetting the environment or from
      the observe function.
      :return: A tuple containing the actual action and additional info on the action
      """
      raise NotImplementedError("")
  
imports: from typing import Union, List, Dict
  import numpy
  from rl_coach.core_types import EnvResponse, ActionInfo, RunPhase, PredictionType, ActionType, Transition
  from rl_coach.saver import SaverCollection
label_desc: Use image node_id 8 for calling the AgentInterface obj's underlying member method code with example usage: obj.act() without return types