code: def __init__(
      self, algorithm, act_dim, e_greed=0.1, e_greed_decrement=0
  ):
      super(Agent, self).__init__(algorithm)
      assert isinstance(act_dim, int)
      self.act_dim = act_dim
  
      self.global_step = 0
      self.update_target_steps = (
          200  # 每隔200个training steps再把model的参数复制到target_model中
      )
  
      self.e_greed = e_greed  # 有一定概率随机选取动作，探索
      self.e_greed_decrement = e_greed_decrement
  
file_path: PARL/examples/tutorials/parl2_dygraph/lesson3/homework/dqn_mountaincar/agent.py
imports: import parl
  import paddle
  import numpy
label_desc: Use image node_id 1 to create a new Agent object from inherited base classes: parl with example: obj = Agent(algorithm, act_dim, e_greed, e_greed_decrement)