algo:
  ddpg:
    params:
      target_update_tau: 0.01
    policy:
      exploration:
        sigma: 0.3
        theta: 0.15
  deterministic_params:
    buffer_batch_size: 32
    min_buffer_size: 10000
    n_train_steps: 500
    qf_lr: 0.0001
    steps_per_epoch: 1
  dqn:
    params:
      clip_gradient: 10
      deterministic_eval: true
      double_q: false
      target_update_freq: 2
    policy:
      exploration:
        decay_ratio: 0.5
        max_epsilon: 1.0
        min_epsilon: 0.05
  general_params:
    discount: 0.99
  package: garage
  policy:
    hidden_sizes:
    - 128
    - 128
    pretrained_policy: null
  ppo:
    params:
      center_adv: false
    tanhnormal: false
  pretrain:
    additional_config: null
    algo_to_pretrain: null
    params:
      episodes_per_batch: 10
      loss: log_prob
      policy_lr: 0.01
    pretrain_algo: rbc
  replay_buffer:
    buffer_size: 200000
  rnd:
    batch_size: 64
    bound_reward_weight: cosine
    bound_reward_weight_initial_ratio: 0.999999
    bound_reward_weight_transient_epochs: 10
    hidden_sizes:
    - 64
    - 64
    intrinsic_reward_weight: 0.0001
    n_train_steps: 32
    output_dim: 128
    predictor_lr: 0.001
    standardize_extrinsic_reward: true
    standardize_intrinsic_reward: true
  sampler:
    n_workers: 16
    type: ray
  train:
    batch_size: 50000
    n_epochs: 100
    steps_per_epoch: 32
  type: ppo
context:
  disable_logging: false
  experiment_name: null
  log_dir:
    from_keys:
    - microgrid.config.scenario
    - microgrid.methods.set_forecaster.forecaster
    - microgrid.methods.set_module_attrs.battery_transition_model
    - context.seed
    - env.domain_randomization.noise_std
    - algo.ppo.tanhnormal
    - algo.rnd.intrinsic_reward_weight
    parent: /home/ahalev/data/GridRL/paper_experiments
    use_existing_dir: false
  seed: 42
  snapshot_gap: 10
  verbose: 0
  wandb:
    api_key_file: ../../local/wandb_api_key.txt
    group: null
    log_density: 1
    plot_baseline:
    - mpc
    - rbc
    username: ahalev
env:
  cls: DiscreteMicrogridEnv
  domain_randomization:
    noise_std: 0.01
    relative_noise: true
  forced_genset: null
  net_load:
    slack_module: genset
    use: true
  observation_keys:
  - soc
  - net_load
  - import_price_current
  - import_price_forecast_0
  - import_price_forecast_1
  - import_price_forecast_2
  - import_price_forecast_3
  - import_price_forecast_4
  - import_price_forecast_5
  - import_price_forecast_6
  - import_price_forecast_7
  - import_price_forecast_8
  - import_price_forecast_9
  - import_price_forecast_10
  - import_price_forecast_11
  - import_price_forecast_12
  - import_price_forecast_13
  - import_price_forecast_14
  - import_price_forecast_15
  - import_price_forecast_16
  - import_price_forecast_17
  - import_price_forecast_18
  - import_price_forecast_19
  - import_price_forecast_20
  - import_price_forecast_21
  - import_price_forecast_22
microgrid:
  attributes:
    reward_shaping_func: !BaselineShaper
      baseline_module: false
      module:
      - genset
      - 0
  config:
    scenario: 9
  methods:
    set_forecaster:
      forecast_horizon: 23
      forecaster: 0.0
      forecaster_increase_uncertainty: true
      forecaster_relative_noise: true
    set_module_attrs:
      battery_transition_model: null
      normalized_action_bounds:
      - 0.0
      - 1.0
  trajectory:
    evaluate:
      final_step: -1
      initial_step: 5840
      trajectory_func: null
    train:
      final_step: 5840
      initial_step: 0
      trajectory_func: !FixedLengthStochasticTrajectory
        trajectory_length: 720
verbose: 1