text: ### RND PPO CartPole Config ###
  
  env = {
      "name": "cartpole",
      "action_type": "discrete",
      "render": False,
  }
  
  agent = {
      "name": "rnd_ppo",
      "network": "discrete_policy_separate_value",
      "gamma": 0.99,
      "batch_size": 64,
      "n_step": 128,
      "n_epoch": 3,
      "_lambda": 0.95,
      "epsilon_clip": 0.1,
      "vf_coef": 0.5,
      "ent_coef": 0.0,
      "clip_grad_norm": 1.0,
      # Parameters for Random Network Distillation
      "rnd_network": "rnd_mlp",  # rnd_mlp, rnd_cnn, rnd_multi
      "gamma_i": 0.99,
      "extrinsic_coeff": 1.0,
      "intrinsic_coeff": 0.001,
      "obs_normalize": True,
      "ri_normalize": True,
      "batch_norm": True,
  }
  
  optim = {
      "name": "adam",
      "lr": 0.0001,
  }
  
  train = {
      "training": True,
      "load_path": None,
      "run_step": 100000,
      "print_period": 1000,
      "save_period": 10000,
      "eval_iteration": 10,
      # distributed setting
      "distributed_batch_size": 512,
      "update_period": agent["n_step"],
      "num_workers": 8,
  }
  