angkul07 commited on
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1 Parent(s): b36257b

mountain car

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README.md CHANGED
@@ -1,7 +1,7 @@
1
  ---
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  library_name: stable-baselines3
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  tags:
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- - LunarLander-v2
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  - deep-reinforcement-learning
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  - reinforcement-learning
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  - stable-baselines3
@@ -12,17 +12,17 @@ model-index:
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  type: reinforcement-learning
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  name: reinforcement-learning
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  dataset:
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- name: LunarLander-v2
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- type: LunarLander-v2
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  metrics:
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  - type: mean_reward
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- value: 259.58 +/- 17.08
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  name: mean_reward
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  verified: false
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  ---
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- # **PPO** Agent playing **LunarLander-v2**
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- This is a trained model of a **PPO** agent playing **LunarLander-v2**
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  using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
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  ## Usage (with Stable-baselines3)
 
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  ---
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  library_name: stable-baselines3
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  tags:
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+ - MountainCarContinuous-v0
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  - deep-reinforcement-learning
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  - reinforcement-learning
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  - stable-baselines3
 
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  type: reinforcement-learning
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  name: reinforcement-learning
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  dataset:
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+ name: MountainCarContinuous-v0
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+ type: MountainCarContinuous-v0
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  metrics:
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  - type: mean_reward
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+ value: -0.00 +/- 0.00
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  name: mean_reward
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  verified: false
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  ---
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+ # **PPO** Agent playing **MountainCarContinuous-v0**
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+ This is a trained model of a **PPO** agent playing **MountainCarContinuous-v0**
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  using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
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  ## Usage (with Stable-baselines3)
config.json CHANGED
@@ -1 +1 @@
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It allows to keep variance\n above zero and prevent it from growing too fast. In practice, ``exp()`` is usually enough.\n :param squash_output: Whether to squash the output using a tanh function,\n this allows to ensure boundaries when using gSDE.\n :param features_extractor_class: Features extractor to use.\n :param features_extractor_kwargs: Keyword arguments\n to pass to the features extractor.\n :param share_features_extractor: If True, the features extractor is shared between the policy and value networks.\n :param normalize_images: Whether to normalize images or not,\n dividing by 255.0 (True by default)\n :param optimizer_class: The optimizer to use,\n ``th.optim.Adam`` by default\n :param optimizer_kwargs: Additional keyword arguments,\n excluding the learning rate, to pass to the optimizer\n ", "__init__": "<function ActorCriticPolicy.__init__ at 0x7f53074f3420>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f53074f34c0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f53074f3560>", 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