class_docstr: Advantage Learning.
  
  See: http://arxiv.org/abs/1512.04860.
  
  Args:
    alpha (float): Weight of (persistent) advantages. Convergence
      is guaranteed only for alpha in [0, 1).
  
  For other arguments, see DQN.
code: def __init__(self, *args, **kwargs):
      self.alpha = kwargs.pop("alpha", 0.9)
      super().__init__(*args, **kwargs)
  
imports: import torch
  from pfrl.agents import dqn
  from pfrl.utils.recurrent import pack_and_forward
label_desc: Use image node_id 1 to create a new AL object from inherited base classes: dqn with example: obj = AL()