Upload PPO LunarLander-v2 trained agent

README.md

@@ -16,7 +16,7 @@ model-index:
       type: LunarLander-v2
     metrics:
     - type: mean_reward
-      value: 264.48 +/- 8.91
+      value: 291.76 +/- 18.32
       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 0x7f7e11fe4160>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f7e11fe41f0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f7e11fe4280>", "_build_mlp_extractor": "<function 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"
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"
     },
     "ep_success_buffer": {
         ":type:": "<class 'collections.deque'>",
         ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
     },
-    "_n_updates": 310,
+    "_n_updates": 1530,
     "n_steps": 2048,
     "gamma": 0.99,
     "gae_lambda": 0.95,

ppo_lunar_lander/policy.optimizer.pth

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ppo_lunar_lander/policy.pth

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results.json

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