Upload first PPO LunarLander-v2 trained agent, reward = 260+/-19

README.md

@@ -10,7 +10,7 @@ model-index:
   results:
   - metrics:
     - type: mean_reward
-      value: 248.23 +/- 24.73
+      value: 291.63 +/- 15.40
       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 0x7f932ab17950>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f932ab179e0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f932ab17a70>", "_build_mlp_extractor": "<function 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"
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"
     },
     "ep_success_buffer": {
         ":type:": "<class 'collections.deque'>",
         ":serialized:": "gASVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
     },
-    "_n_updates": 248,
+    "_n_updates": 616,
     "n_steps": 1024,
     "gamma": 0.999,
     "gae_lambda": 0.98,

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replay.mp4

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results.json

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