Upload PPO LunarLander-v2 trained agent

README.md

@@ -10,7 +10,7 @@ model-index:
   results:
   - metrics:
     - type: mean_reward
-      value: 252.46 +/- 21.38
+      value: 285.84 +/- 19.92
       name: mean_reward
     task:
       type: reinforcement-learning

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 0x7f2185899560>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f21858995f0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f2185899680>", "_build_mlp_extractor": "<function 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"
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     },
     "ep_success_buffer": {
         ":type:": "<class 'collections.deque'>",
         ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
     },
-    "_n_updates": 124,
+    "_n_updates": 372,
     "n_steps": 1024,
     "gamma": 0.999,
     "gae_lambda": 0.98,

ppo-LunarLander-v2/policy.optimizer.pth

@@ -1,3 +1,3 @@
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ppo-LunarLander-v2/policy.pth

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results.json

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