Upload PPO LunarLander-v2 trained agent

README.md

@@ -10,7 +10,7 @@ model-index:
   results:
   - metrics:
     - type: mean_reward
-      value: 208.67 +/- 41.69
+      value: 286.33 +/- 13.08
       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 0x7ff8db0f85f0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7ff8db0f8680>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7ff8db0f8710>", "_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_steps": 1024,
-    "gamma": 0.999,
+    "_n_updates": 468,
+    "n_steps": 2048,
+    "gamma": 0.995,
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     "ent_coef": 0.01,
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