text: import sys
  sys.path.append('.')
  
  
  from abstract_rl.src.run.run_trpo import run_trpo
  
  run_config = {
  
      # simulations settings
      'num_epochs': 1000,
      'max_steps': 10000,
      'reload': False,
      'seed': 17,
  
      'env_name': 'Qube-v0',
      # 'env_name': 'QubeRR-v0',
      'env_discount': 0.995,
      'env_normalize': True,
      'env_center_states': False,
      'env_num_threads': 1,
      'env_render': False,
  
      # fully connected neural q function
      'val_struct': [64, 64],
      'val_lr': 0.00001,
      'val_steps_per_epoch': 50,
      'val_layer_norm': False,
      'val_act_fn': ['tanh', 'tanh', 'none'],
      'val_init': 'xavier_gaussian',
      'val_batch_size': 64,
      'val_sync_steps': 1,
      'val_l2_reg': 0.001,
  
      # advantage settings
      'gae_lambda': 0.97,
  
      # policy network structure
      'policy_structure': [64, 64],
      'policy_act_fn': ['tanh', 'tanh', ['none', 'softplus']],
      'policy_layer_norm': False,
      'policy_opt_steps': 5,
      'policy_init': 'gaussian',
      'policy_sync_steps': 1,
      'policy_batch_size': 16392,
      'policy_sigma': 1.0,
      'policy_cov_type': 'single',
      'filter_states': False,
      'filter_rewards': False,
  
      # settings for trpo
      'n_bootstrap_steps': 50,
      'trpo_cg_max_k': 10,
      'trpo_cg_res_tol': 1e-10,
      'trpo_dvp_damping': 0.1,
      'trpo_tr_eps': 0.001
  
  }
  run_trpo(run_config)
  