PPO in lunar lander with (~15h of) tunning of hyperparams

PPO-LunarLander-v2.zip

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PPO-LunarLander-v2/_stable_baselines3_version

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PPO-LunarLander-v2/data

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PPO-LunarLander-v2/policy.optimizer.pth

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+size 87929

PPO-LunarLander-v2/policy.pth

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+size 43201

PPO-LunarLander-v2/pytorch_variables.pth

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PPO-LunarLander-v2/system_info.txt

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+OS: Linux-5.15.0-53-generic-x86_64-with-glibc2.29 #59~20.04.1-Ubuntu SMP Thu Oct 20 15:10:22 UTC 2022
+Python: 3.8.10
+Stable-Baselines3: 1.6.2
+PyTorch: 1.13.0+cu117
+GPU Enabled: True
+Numpy: 1.23.5
+Gym: 0.21.0

README.md

@@ -16,7 +16,7 @@ model-index:
       type: LunarLander-v2
     metrics:
     - type: mean_reward
-      value: 265.20 +/- 23.34
+      value: 278.73 +/- 20.17
       name: mean_reward
       verified: false
 ---

config.json

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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 0x7fe041216280>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fe041216310>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fe0412163a0>", "_build_mlp_extractor": "<function 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results.json

@@ -1 +1 @@
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