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a2c-CartPole-v1

Reinforcement Learning
rl-algo-impls
CartPole-v1
a2c
deep-reinforcement-learning
Eval Results
Model card Files Community
a2c-CartPole-v1
File size: 3,004 Bytes 
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CartPole-v1: &cartpole-defaults
  n_timesteps: !!float 5e4
  env_hyperparams:
    rolling_length: 50
  policy_hyperparams:
    hidden_sizes: [256, 256]
  algo_hyperparams:
    learning_rate: !!float 2.3e-3
    batch_size: 64
    buffer_size: 100000
    learning_starts: 1000
    gamma: 0.99
    target_update_interval: 10
    train_freq: 256
    gradient_steps: 128
    exploration_fraction: 0.16
    exploration_final_eps: 0.04
  eval_hyperparams:
    step_freq: !!float 1e4

CartPole-v0:
  <<: *cartpole-defaults
  n_timesteps: !!float 4e4

MountainCar-v0:
  n_timesteps: !!float 1.2e5
  env_hyperparams:
    rolling_length: 50
  policy_hyperparams:
    hidden_sizes: [256, 256]
  algo_hyperparams:
    learning_rate: !!float 4e-3
    batch_size: 128
    buffer_size: 10000
    learning_starts: 1000
    gamma: 0.98
    target_update_interval: 600
    train_freq: 16
    gradient_steps: 8
    exploration_fraction: 0.2
    exploration_final_eps: 0.07

Acrobot-v1:
  n_timesteps: !!float 1e5
  env_hyperparams:
    rolling_length: 50
  policy_hyperparams:
    hidden_sizes: [256, 256]
  algo_hyperparams:
    learning_rate: !!float 6.3e-4
    batch_size: 128
    buffer_size: 50000
    learning_starts: 0
    gamma: 0.99
    target_update_interval: 250
    train_freq: 4
    gradient_steps: -1
    exploration_fraction: 0.12
    exploration_final_eps: 0.1

LunarLander-v2:
  n_timesteps: !!float 5e5
  env_hyperparams:
    rolling_length: 50
  policy_hyperparams:
    hidden_sizes: [256, 256]
  algo_hyperparams:
    learning_rate: !!float 1e-4
    batch_size: 256
    buffer_size: 100000
    learning_starts: 10000
    gamma: 0.99
    target_update_interval: 250
    train_freq: 8
    gradient_steps: -1
    exploration_fraction: 0.12
    exploration_final_eps: 0.1
    max_grad_norm: 0.5
  eval_hyperparams:
    step_freq: 25_000

_atari: &atari-defaults
  n_timesteps: !!float 1e7
  env_hyperparams:
    frame_stack: 4
    no_reward_timeout_steps: 1_000
    no_reward_fire_steps: 500
    n_envs: 8
    vec_env_class: async
  algo_hyperparams:
    buffer_size: 100000
    learning_rate: !!float 1e-4
    batch_size: 32
    learning_starts: 100000
    target_update_interval: 1000
    train_freq: 8
    gradient_steps: 2
    exploration_fraction: 0.1
    exploration_final_eps: 0.01
  eval_hyperparams:
    deterministic: false

PongNoFrameskip-v4:
  <<: *atari-defaults
  n_timesteps: !!float 2.5e6

_impala-atari: &impala-atari-defaults
  <<: *atari-defaults
  policy_hyperparams:
    cnn_style: impala
    cnn_flatten_dim: 256
    init_layers_orthogonal: true
    cnn_layers_init_orthogonal: false

impala-PongNoFrameskip-v4:
  <<: *impala-atari-defaults
  env_id: PongNoFrameskip-v4
  n_timesteps: !!float 2.5e6

impala-BreakoutNoFrameskip-v4:
  <<: *impala-atari-defaults
  env_id: BreakoutNoFrameskip-v4

impala-SpaceInvadersNoFrameskip-v4:
  <<: *impala-atari-defaults
  env_id: SpaceInvadersNoFrameskip-v4

impala-QbertNoFrameskip-v4:
  <<: *impala-atari-defaults
  env_id: QbertNoFrameskip-v4