DRL

README.md

@@ -16,7 +16,7 @@ model-index:
       type: LunarLander-v2
     metrics:
     - type: mean_reward
-      value: 271.36 +/- 14.18
+      value: 267.03 +/- 17.57
       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 0x7f0bef5c0ca0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f0bef5c0d30>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f0bef5c0dc0>", "_build_mlp_extractor": "<function 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     "ep_success_buffer": {
         ":type:": "<class 'collections.deque'>",
         ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
     },
-    "_n_updates": 248,
+    "_n_updates": 368,
     "n_steps": 1024,
-    "gamma": 0.999,
+    "gamma": 0.99,
     "gae_lambda": 0.98,
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     "vf_coef": 0.5,

my_first_model/policy.optimizer.pth

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-size 88057
+oid sha256:b6f482adf75f21b7a07eeca741cd5df6eac1bbf4c584634b96b2f8d06ac36352
+size 87929

my_first_model/policy.pth

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+oid sha256:642e3a7286ffbe860ff51abcb063de719cbb381de7662f36c4a3bec6abffb657
 size 43201

results.json

@@ -1 +1 @@
-{"mean_reward": 271.36367060612554, "std_reward": 14.179622846680294, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-12-18T13:23:47.188704"}
+{"mean_reward": 267.03281409645405, "std_reward": 17.570888320321533, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-12-18T14:17:58.167466"}