andyleow commited on
Commit
84101bf
1 Parent(s): 0cc4712

Upload PPO LunarLander-v2 trained agent

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README.md CHANGED
@@ -6,7 +6,7 @@ tags:
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  - reinforcement-learning
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  - stable-baselines3
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  model-index:
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- - name: PPO-MLPPolicy
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  results:
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  - task:
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  type: reinforcement-learning
@@ -16,13 +16,13 @@ model-index:
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  type: LunarLander-v2
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  metrics:
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  - type: mean_reward
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- value: 218.52 +/- 46.23
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  name: mean_reward
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  verified: false
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  ---
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- # **PPO-MLPPolicy** Agent playing **LunarLander-v2**
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- This is a trained model of a **PPO-MLPPolicy** 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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  - reinforcement-learning
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  - stable-baselines3
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  model-index:
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+ - name: PPO
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  results:
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  - task:
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  type: reinforcement-learning
 
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  type: LunarLander-v2
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  metrics:
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  - type: mean_reward
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+ value: 251.68 +/- 13.13
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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)
config.json CHANGED
@@ -1 +1 @@
1
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If None, the latent features from the policy will be used.\n Pass an empty list to use the states as features.\n :param use_expln: Use ``expln()`` function instead of ``exp()`` to ensure\n a positive standard deviation (cf paper). 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 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 0x7f7793136040>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f77931360d0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f7793136160>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f77931361f0>", "_build": "<function 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