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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def rlmb_dqn_base():
 """rlmb_dqn_base params."""

  hparams = _rlmb_base()
  simulated_rollout_length = 10
  dqn_params = dict(
      base_algo="dqn",
      base_algo_params="dqn_original_params",
      real_batch_size=1,
      simulated_batch_size=16,
      dqn_agent_generates_trainable_dones=False,
      eval_batch_size=1,
      # Must be equal to dqn_time_limit for now
      simulated_rollout_length=simulated_rollout_length,
      dqn_time_limit=simulated_rollout_length,
      simulation_flip_first_random_for_beginning=False,
      dqn_eval_episodes_num=3,

      # TODO(kc): only for model-free compatibility, remove this
      epochs_num=-1,
  )
  update_hparams(hparams, dqn_params)
  return hparams