class_docstr: Base class for defining an agent.
docstr: Observe one transition and choose an action.
  
  Args:
      reward (float) : amount of reward returned after previous action.
      next_state (object): observation provided by the environment.
  
  Returns:
      action (int): action choosen by agent.
      debug_info (dict): auxiliary diagnostic information.
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code: def step(self, reward, next_state):
      """
      Observe one transition and choose an action.
  
      Args:
          reward (float) : amount of reward returned after previous action.
          next_state (object): observation provided by the environment.
  
      Returns:
          action (int): action choosen by agent.
          debug_info (dict): auxiliary diagnostic information.
      """
      pass
  
imports: from abc import ABCMeta, abstractmethod
  import numpy
  from importlib import import_module
  from .shared.discretize import BoxSpaceDiscretizer
label_desc: Use image node_id 3 for calling the AgentBaseClass obj's underlying member method code with example usage: obj.step(reward, next_state) without return types