PPO LunarLander-v2 agent

README.md

@@ -16,7 +16,7 @@ model-index:
       type: LunarLander-v2
     metrics:
     - type: mean_reward
-      value: 275.24 +/- 14.14
+      value: 253.96 +/- 20.84
       name: mean_reward
       verified: false
 ---

config.json

@@ -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 0x7ff5a4869d30>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7ff5a4869dc0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7ff5a4869e50>", "_build_mlp_extractor": "<function 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ppo-LunarLander-v2-jjs/_stable_baselines3_version

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ppo-LunarLander-v2-jjs/data

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+- Python: 3.10.12
+- Stable-Baselines3: 2.0.0a5
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+- GPU Enabled: True
+- Numpy: 1.23.5
+- Cloudpickle: 2.2.1
+- Gymnasium: 0.28.1
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