Upload PPO LunarLander-v2 trained agent

README.md

@@ -16,7 +16,7 @@ model-index:
       type: LunarLander-v2
     metrics:
     - type: mean_reward
-      value: 221.81 +/- 74.96
+      value: 287.94 +/- 14.23
       name: mean_reward
       verified: false
 ---

config.json

@@ -1 +1 @@
-{"policy_class": {":type:": "<class 'abc.ABCMeta'>", ":serialized:": "gAWVOwAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMEUFjdG9yQ3JpdGljUG9saWN5lJOULg==", "__module__": "stable_baselines3.common.policies", "__doc__": "\n    Policy class for actor-critic algorithms (has both policy and value prediction).\n    Used by A2C, PPO and the likes.\n\n    :param observation_space: Observation space\n    :param action_space: Action space\n    :param lr_schedule: Learning rate schedule (could be constant)\n    :param net_arch: The specification of the policy and value networks.\n    :param activation_fn: Activation function\n    :param ortho_init: Whether to use or not orthogonal initialization\n    :param use_sde: Whether to use State Dependent Exploration or not\n    :param log_std_init: Initial value for the log standard deviation\n    :param full_std: Whether to use (n_features x n_actions) parameters\n        for the std instead of only (n_features,) when using gSDE\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 share_features_extractor: If True, the features extractor is shared between the policy and value networks.\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 0x7f4cf6b17130>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f4cf6b171c0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f4cf6b17250>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f4cf6b172e0>", "_build": "<function ActorCriticPolicy._build at 0x7f4cf6b17370>", "forward": "<function ActorCriticPolicy.forward at 0x7f4cf6b17400>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f4cf6b17490>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f4cf6b17520>", "_predict": "<function ActorCriticPolicy._predict at 0x7f4cf6b175b0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f4cf6b17640>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f4cf6b176d0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f4cf6b17760>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f4cf6b1c380>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1685498801276898913, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "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"}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.015808000000000044, "_stats_window_size": 100, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 248, "observation_space": {":type:": "<class 'gymnasium.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "bounded_below": "[ True  True  True  True  True  True  True  True]", "bounded_above": "[ True  True  True  True  True  True  True  True]", "_shape": [8], "low": "[-90.        -90.         -5.         -5.         -3.1415927  -5.\n  -0.         -0.       ]", "high": "[90.        90.         5.         5.         3.1415927  5.\n  1.         1.       ]", "low_repr": "[-90.        -90.         -5.         -5.         -3.1415927  -5.\n  -0.         -0.       ]", "high_repr": "[90.        90.         5.         5.         3.1415927  5.\n  1.         1.       ]", "_np_random": null}, "action_space": {":type:": "<class 'gymnasium.spaces.discrete.Discrete'>", ":serialized:": "gAWV1QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCloCmgOjApfbnBfcmFuZG9tlE51Yi4=", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "n_steps": 1024, "gamma": 0.999, "gae_lambda": 0.98, "ent_coef": 0.01, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 64, "n_epochs": 4, "clip_range": {":type:": "<class 'function'>", ":serialized:": "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"}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "system_info": {"OS": "Linux-5.15.107+-x86_64-with-glibc2.31 # 1 SMP Sat Apr 29 09:15:28 UTC 2023", "Python": "3.10.11", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.0.1+cu118", "GPU Enabled": "True", "Numpy": "1.22.4", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}
+{"policy_class": {":type:": "<class 'abc.ABCMeta'>", ":serialized:": "gAWVOwAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMEUFjdG9yQ3JpdGljUG9saWN5lJOULg==", "__module__": "stable_baselines3.common.policies", "__doc__": "\n    Policy class for actor-critic algorithms (has both policy and value prediction).\n    Used by A2C, PPO and the likes.\n\n    :param observation_space: Observation space\n    :param action_space: Action space\n    :param lr_schedule: Learning rate schedule (could be constant)\n    :param net_arch: The specification of the policy and value networks.\n    :param activation_fn: Activation function\n    :param ortho_init: Whether to use or not orthogonal initialization\n    :param use_sde: Whether to use State Dependent Exploration or not\n    :param log_std_init: Initial value for the log standard deviation\n    :param full_std: Whether to use (n_features x n_actions) parameters\n        for the std instead of only (n_features,) when using gSDE\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 share_features_extractor: If True, the features extractor is shared between the policy and value networks.\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 0x7facd9b8a440>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7facd9b8a4d0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7facd9b8a560>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7facd9b8a5f0>", "_build": "<function ActorCriticPolicy._build at 0x7facd9b8a680>", "forward": "<function ActorCriticPolicy.forward at 0x7facd9b8a710>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7facd9b8a7a0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7facd9b8a830>", "_predict": "<function ActorCriticPolicy._predict at 0x7facd9b8a8c0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7facd9b8a950>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7facd9b8a9e0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7facd9b8aa70>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7facd9b7de40>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 3014656, "_total_timesteps": 3000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1685557842207360443, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "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"}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.004885333333333408, "_stats_window_size": 100, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 736, "observation_space": {":type:": "<class 'gymnasium.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "bounded_below": "[ True  True  True  True  True  True  True  True]", "bounded_above": "[ True  True  True  True  True  True  True  True]", "_shape": [8], "low": "[-90.        -90.         -5.         -5.         -3.1415927  -5.\n  -0.         -0.       ]", "high": "[90.        90.         5.         5.         3.1415927  5.\n  1.         1.       ]", "low_repr": "[-90.        -90.         -5.         -5.         -3.1415927  -5.\n  -0.         -0.       ]", "high_repr": "[90.        90.         5.         5.         3.1415927  5.\n  1.         1.       ]", "_np_random": null}, "action_space": {":type:": "<class 'gymnasium.spaces.discrete.Discrete'>", ":serialized:": "gAWV1QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCloCmgOjApfbnBfcmFuZG9tlE51Yi4=", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "n_steps": 1024, "gamma": 0.999, "gae_lambda": 0.98, "ent_coef": 0.01, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 64, "n_epochs": 4, "clip_range": {":type:": "<class 'function'>", ":serialized:": "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"}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "gAWVxQIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTAvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUjARmdW5jlEuEQwIEAZSMA3ZhbJSFlCl0lFKUfZQojAtfX3BhY2thZ2VfX5SMGHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbpSMCF9fbmFtZV9flIwec3RhYmxlX2Jhc2VsaW5lczMuY29tbW9uLnV0aWxzlIwIX19maWxlX1+UjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjEwL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaB99lH2UKGgWaA2MDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgXjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz8zqSowVTJhhZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"}, "system_info": {"OS": "Linux-5.15.107+-x86_64-with-glibc2.31 # 1 SMP Sat Apr 29 09:15:28 UTC 2023", "Python": "3.10.11", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.0.1+cu118", "GPU Enabled": "True", "Numpy": "1.22.4", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}

ppo-LunarLander-v2.zip

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:a14b66b887384162ca848608be7d3ace48dd59f732adf5690920e6e94f670453
-size 146731
+oid sha256:0c9aa776dbcbc1cf72f93cdb072d61ec9bc5028c10923bb02bc41ebe991929a2
+size 146635

ppo-LunarLander-v2/data

@@ -4,34 +4,34 @@
         ":serialized:": "gAWVOwAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMEUFjdG9yQ3JpdGljUG9saWN5lJOULg==",
         "__module__": "stable_baselines3.common.policies",
         "__doc__": "\n    Policy class for actor-critic algorithms (has both policy and value prediction).\n    Used by A2C, PPO and the likes.\n\n    :param observation_space: Observation space\n    :param action_space: Action space\n    :param lr_schedule: Learning rate schedule (could be constant)\n    :param net_arch: The specification of the policy and value networks.\n    :param activation_fn: Activation function\n    :param ortho_init: Whether to use or not orthogonal initialization\n    :param use_sde: Whether to use State Dependent Exploration or not\n    :param log_std_init: Initial value for the log standard deviation\n    :param full_std: Whether to use (n_features x n_actions) parameters\n        for the std instead of only (n_features,) when using gSDE\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 share_features_extractor: If True, the features extractor is shared between the policy and value networks.\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 0x7f4cf6b17130>",
-        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f4cf6b171c0>",
-        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f4cf6b17250>",
-        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f4cf6b172e0>",
-        "_build": "<function ActorCriticPolicy._build at 0x7f4cf6b17370>",
-        "forward": "<function ActorCriticPolicy.forward at 0x7f4cf6b17400>",
-        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f4cf6b17490>",
-        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f4cf6b17520>",
-        "_predict": "<function ActorCriticPolicy._predict at 0x7f4cf6b175b0>",
-        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f4cf6b17640>",
-        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f4cf6b176d0>",
-        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f4cf6b17760>",
+        "__init__": "<function ActorCriticPolicy.__init__ at 0x7facd9b8a440>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7facd9b8a4d0>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7facd9b8a560>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7facd9b8a5f0>",
+        "_build": "<function ActorCriticPolicy._build at 0x7facd9b8a680>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7facd9b8a710>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7facd9b8a7a0>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7facd9b8a830>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7facd9b8a8c0>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7facd9b8a950>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7facd9b8a9e0>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7facd9b8aa70>",
         "__abstractmethods__": "frozenset()",
-        "_abc_impl": "<_abc._abc_data object at 0x7f4cf6b1c380>"
+        "_abc_impl": "<_abc._abc_data object at 0x7facd9b7de40>"
     },
     "verbose": 1,
     "policy_kwargs": {},
-    "num_timesteps": 1015808,
-    "_total_timesteps": 1000000,
+    "num_timesteps": 3014656,
+    "_total_timesteps": 3000000,
     "_num_timesteps_at_start": 0,
     "seed": null,
     "action_noise": null,
-    "start_time": 1685498801276898913,
+    "start_time": 1685557842207360443,
     "learning_rate": 0.0003,
     "tensorboard_log": null,
     "_last_obs": {
         ":type:": "<class 'numpy.ndarray'>",
-        ":serialized:": "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"
+        ":serialized:": "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"
     },
     "_last_episode_starts": {
         ":type:": "<class 'numpy.ndarray'>",
@@ -41,17 +41,17 @@
     "_episode_num": 0,
     "use_sde": false,
     "sde_sample_freq": -1,
-    "_current_progress_remaining": -0.015808000000000044,
+    "_current_progress_remaining": -0.004885333333333408,
     "_stats_window_size": 100,
     "ep_info_buffer": {
         ":type:": "<class 'collections.deque'>",
-        ":serialized:": "gAWVMAwAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpRHQHEMsqnWJ7+MAWyUTR8BjAF0lEdAk1mGa+evp3V9lChoBkdAcQ5y1eBxxWgHTSABaAhHQJNZsCtA9mp1fZQoaAZHQG0/VjRUm2NoB00AAWgIR0CTWpbADaGpdX2UKGgGR0Bx7+Ezwc5saAdNMwFoCEdAk1tkFnqVyHV9lChoBkdAcAsrrgOz6mgHTSEBaAhHQJNb2RHPNV11fZQoaAZHQHIC2zv7WNFoB00RAWgIR0CTW+bO/tY0dX2UKGgGR0ByPwbIcR16aAdNBQFoCEdAk10Ut/WlM3V9lChoBkdAQuVv/BFd9mgHS/9oCEdAk10UbkwN9nV9lChoBkdAcY1/EfkmyGgHTSIBaAhHQJNdjfixVyZ1fZQoaAZHQHETT+717IFoB01LAWgIR0CTXlriEQGwdX2UKGgGR0Bw8vIPsiSraAdNFwFoCEdAk16ATdtVJnV9lChoBkdAcabbD/EOy2gHTQ8BaAhHQJNe6uMdcSp1fZQoaAZHQHEdGUSqU/xoB00gAWgIR0CTX/lUIcBEdX2UKGgGR0BxaQKlYU35aAdNAwFoCEdAk2BcKTjebnV9lChoBkdAbuZSWJJoTWgHTeMBaAhHQJNgtk+X7ch1fZQoaAZHQHBwPy08eS1oB00dAWgIR0CTYcKQ7tAtdX2UKGgGR0BxP1nf2saLaAdNKwFoCEdAk2HLmlqJuXV9lChoBkdAchDd1MdtEWgHS/9oCEdAk2IL9uP3jHV9lChoBkdAcqT8+iaiK2gHTR4BaAhHQJNjuGwiaAp1fZQoaAZHQHJygLApKBdoB00bAWgIR0CTZC1rZamodX2UKGgGR0Bx16gL7XQMaAdL/WgIR0CTZISUTtb+dX2UKGgGR0BwfQDdP+GXaAdNLQFoCEdAk2S26XjU/nV9lChoBkdAbufG2CuloGgHS+hoCEdAk2UoQ8OkL3V9lChoBkdAcY81xbSql2gHTQ0BaAhHQJNlaG34Kx91fZQoaAZHQG5zxF7Uoa1oB00tAWgIR0CTZd19ORDDdX2UKGgGR0Bx/Yyj59E1aAdL/mgIR0CTZlD4xk/bdX2UKGgGR0BulY66reZYaAdNHQFoCEdAk2bATM7lrHV9lChoBkdAb3uJXyRSxmgHTRwBaAhHQJNoUHTqjah1fZQoaAZHQG1OxKHwgDBoB00eAWgIR0CTaMCA+Y+jdX2UKGgGR0BuC/gpBomHaAdL8GgIR0CTaMp7kXDWdX2UKGgGR0BxHln5BTn8aAdNIAFoCEdAk2klloUSI3V9lChoBkdAckZhqTKT0WgHTQYBaAhHQJNpVwHZ9NN1fZQoaAZHQHAzI1LrX19oB00kAWgIR0CTamVvddmhdX2UKGgGR0BGVmd7OVxCaAdL0WgIR0CTavpCa7VbdX2UKGgGR0By3mj1wo9caAdNCQFoCEdAk2tF0tAcDXV9lChoBkdAbowYxcmjTWgHS/xoCEdAk2ugskIHDHV9lChoBkdAcsDe5nUUf2gHTQgBaAhHQJNrtSl3yI51fZQoaAZHQHDyv6j3225oB00qAWgIR0CTbSTfR/mUdX2UKGgGR0BskjY5DJEIaAdNEQFoCEdAk20oLCvX9XV9lChoBkdAbsIKTjebeGgHTQkBaAhHQJNtZudf9gp1fZQoaAZHQHAWIOlO45NoB0vwaAhHQJNtl2q1gIB1fZQoaAZHQHEsOfVZs9BoB00IAWgIR0CTbckPMB6sdX2UKGgGR0Bx6W5I6KceaAdNDAFoCEdAk4UsWO6un3V9lChoBkdAb0KFPBSDRWgHTR8BaAhHQJOFVyJbdJt1fZQoaAZHQHMd/YSQHRloB00xAWgIR0CThliS7oStdX2UKGgGR0BvwD5M10koaAdNKwFoCEdAk4aSzLOiWXV9lChoBkdAcEf24NI9T2gHTS4BaAhHQJOG6BWgezV1fZQoaAZHQHGJihvitJZoB00tAWgIR0CTiCTmnwXqdX2UKGgGR0ByHkgSvkimaAdNHgFoCEdAk4hgZ4wAVHV9lChoBkdAcChUqhDgImgHTQwBaAhHQJOIiuOjqOd1fZQoaAZHQGsR3bVSXMRoB00dAWgIR0CTiP/1g6U8dX2UKGgGR7/SyJbdJrckaAdL4mgIR0CTiRHjp9qldX2UKGgGR0BxaITZg5R1aAdNRQFoCEdAk4nc/IKc/nV9lChoBkdAb37YL9deIGgHTRIBaAhHQJOKOKgqVhV1fZQoaAZHQHBbZaaCtihoB00WAWgIR0CTilPn0TURdX2UKGgGR0ByA3sVtXPraAdNIQFoCEdAk4sOXu3MIXV9lChoBkdAcA2XDWK/EmgHTSkBaAhHQJOLfcBU70Z1fZQoaAZHQFyQ7b+Lm6poB03oA2gIR0CTi4qAz544dX2UKGgGR0BtoVKPGQ0XaAdNCAFoCEdAk4zbF4s3AHV9lChoBkdAcfNb48EFGGgHS/JoCEdAk42F8XvYvnV9lChoBkdAcpEHSnccl2gHTQoBaAhHQJOOAP8Q7Ld1fZQoaAZHQFFymkFfReFoB0vQaAhHQJOPpg4Otnx1fZQoaAZHQEGMlxffGdZoB0vaaAhHQJOQFnoPkJd1fZQoaAZHQG5PIX0oSctoB00xAWgIR0CTkK2Dg62fdX2UKGgGR0Bv4MKJEYwZaAdNZQFoCEdAk5C18kUsWnV9lChoBkdAcL7H8TBZZGgHTQ8BaAhHQJOQ2SIP9UF1fZQoaAZHQHFdZGax5cFoB00dAWgIR0CTkYzEaVD8dX2UKGgGR0BydlSIgvDhaAdNJAFoCEdAk5GeejEehnV9lChoBkdAU7fsUqQRw2gHS8toCEdAk5IlFYuCgHV9lChoBkdAcY5pWV/tpmgHTQ8BaAhHQJOSUvRJEpl1fZQoaAZHQHFfwQQL/jtoB0vzaAhHQJOTHsMRYih1fZQoaAZHQHJnz2rXDm9oB00gAWgIR0CTkyo3Jgb7dX2UKGgGR0BsfBBX0XgtaAdNEgFoCEdAk5ODiKiwjnV9lChoBkdAb6Wq7ROUMWgHTVABaAhHQJOURLOAy2x1fZQoaAZHQG9ZOZCv5gxoB00SAWgIR0CTlTVIZqEfdX2UKGgGR0BzKZx1gYxdaAdNGgFoCEdAk5YQLeANG3V9lChoBkdASDwksz2vjmgHS+FoCEdAk5aD2i+L33V9lChoBkdAcd+G5+Ytx2gHS+9oCEdAk5byFCb+cnV9lChoBkdAcrX4gieNDWgHTTgBaAhHQJOXZl05lvt1fZQoaAZHQHCzBq46Oo5oB00oAWgIR0CTmAvCdjG2dX2UKGgGR0BxWfwd8zAOaAdL/WgIR0CTmE3Kji4sdX2UKGgGR0Bze9BUrCm/aAdNHQFoCEdAk5hp1RtP6HV9lChoBkdAa7Rj8UEgXGgHTQsBaAhHQJOYnmeUY9B1fZQoaAZHQHFnJ+MIeHVoB01QAWgIR0CTmMVdX1aodX2UKGgGR0Bx8NIiC8ODaAdNKwFoCEdAk5ov7N0NjXV9lChoBkdAcgdMeOn2qWgHTSQBaAhHQJOa6oaUA1h1fZQoaAZHQHB7yyUs4DNoB004AWgIR0CTm+Sw4bS7dX2UKGgGR0BxCxTisGPgaAdNVwFoCEdAk5xfnfVI7XV9lChoBkdAUMZ4jbBXS2gHS8VoCEdAk5zdLUTcqXV9lChoBkdAcZfGRmseXGgHTSMBaAhHQJOdV9y925h1fZQoaAZHQHBawwblzU9oB00MAWgIR0CTnZnfVI7OdX2UKGgGR0BwnhK5CngpaAdNsgFoCEdAk53544ZMtnV9lChoBkdAcUpidat9yGgHTRsBaAhHQJOeg3kxREZ1fZQoaAZHQHDHgb+98JFoB0v3aAhHQJOf3v9cbBJ1fZQoaAZHQHDGRhYvFm5oB006AWgIR0CTn+8xbjcVdX2UKGgGR0BvUCx/ustDaAdNAwFoCEdAk6AKqOtGNXV9lChoBkdAcKRdweeWfWgHTRMBaAhHQJOgLA44p+d1fZQoaAZHQG8k611GLDRoB00qAWgIR0CToI9pAUtadX2UKGgGR0BtQZhUipvQaAdNRAFoCEdAk6GcunMt9XV9lChoBkdAcMZNke6qbWgHTQUBaAhHQJOhy0dBBzF1ZS4="
+        ":serialized:": "gAWV6AsAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpRHQHOb3AAQxviMAWyUS9GMAXSUR0Cmm3keQuEmdX2UKGgGR0Bx3p4iX6ZZaAdL4WgIR0CmnM7YbsF/dX2UKGgGR0BxijfixVyWaAdL9GgIR0CmnT5ZbILgdX2UKGgGR0BynTrSmZVoaAdL6WgIR0CmndXVCojwdX2UKGgGR0BzG0zDXOGCaAdNCgFoCEdApp3t/jKgZnV9lChoBkdAcVFQJHAh0WgHS89oCEdApp4Oqm0mdHV9lChoBkdAcCEHG0eEI2gHS9VoCEdApp4wzBRAKXV9lChoBkdAcu8HGjsUqWgHS9JoCEdApp5TgydnTXV9lChoBkdAcLdKnNxEOWgHS+doCEdApp5aQRwqAnV9lChoBkdAcNuwAU+LWWgHS9poCEdApp6wFX7tRnV9lChoBkdAcupwXIlt0mgHS/JoCEdApp7fN3W4E3V9lChoBkdAbhUxzq8lHGgHS+JoCEdApp/zKNhmXnV9lChoBkdAcKhPtUn5SGgHS/doCEdApp/+e4Cp33V9lChoBkdAc1nH2AXl82gHS9poCEdApqAYraufVnV9lChoBkdAc+mQnQY1pGgHTQcBaAhHQKagZhOP/711fZQoaAZHQHGVeVX3g1poB0vPaAhHQKahZV/c32p1fZQoaAZHQHEyBsMy8BdoB0vqaAhHQKaig+L3sX11fZQoaAZHQG38r876pHZoB0vjaAhHQKai0kpI+W51fZQoaAZHQHLiJ5Rjz7NoB0vSaAhHQKai3o6CDmN1fZQoaAZHQHFisKTjebdoB0vSaAhHQKai4zjWCmN1fZQoaAZHQHEiU9lmOENoB0vdaAhHQKai9LFn7Hh1fZQoaAZHQHFfhoIv8IloB0viaAhHQKai8EAYHgR1fZQoaAZHQHK5OGCZnctoB00IAWgIR0Cmo2iBGx2TdX2UKGgGR0Bx7eMkyDZlaAdL7WgIR0Cmo4GfPHDKdX2UKGgGR0ByadVJcxCZaAdL0mgIR0CmpAya/h2odX2UKGgGR0ByyqOdXko4aAdL1mgIR0CmpAnuy/sWdX2UKGgGR0BwMxfAsTWYaAdL2WgIR0CmpA8TrVvudX2UKGgGR0ByOrpQk5ZKaAdNDgFoCEdApqQhtvXK83V9lChoBkdAciVtcv/R3WgHS+FoCEdApqRtQ/HHWHV9lChoBkdAckg2a2F36mgHTbkDaAhHQKatiqslsxh1fZQoaAZHQHGvJ9mYjSpoB0v8aAhHQKatzpQDV6N1fZQoaAZHQHHuPRJEpiJoB0vaaAhHQKauB7jT8YR1fZQoaAZHQG2QRYq5LAZoB0vVaAhHQKauQOCoS+R1fZQoaAZHQHDU27jDKo1oB0vUaAhHQKauUi0OVgR1fZQoaAZHQG4eX8wYcedoB0viaAhHQKauZvOQhfV1fZQoaAZHQG665OSGJvZoB0vgaAhHQKaubaWX1J11fZQoaAZHQHHkOUhV2idoB0vkaAhHQKauhL7oB7x1fZQoaAZHQHLiiOJcgQpoB0vYaAhHQKau4xM36yl1fZQoaAZHQHMsxGtp22ZoB0v1aAhHQKavL/Tb3491fZQoaAZHQHCDIa99MK1oB0vSaAhHQKavTS9du511fZQoaAZHQHF6jiXIEKVoB0vSaAhHQKavSlUIcBF1fZQoaAZHQHGFHyRSxaBoB0vfaAhHQKaviv3ai9J1fZQoaAZHQHLUz+BH09RoB0voaAhHQKavl9KEnLJ1fZQoaAZHQG6tM9r433poB0vdaAhHQKav1HWjGkx1fZQoaAZHQHJaCqABkqdoB0vfaAhHQKawoEwnH/91fZQoaAZHQHNFVQQ+UyJoB0vRaAhHQKawrpMYdhl1fZQoaAZHQHLz2aYu01JoB0vGaAhHQKaw//tpmEp1fZQoaAZHQHHW0euFHrhoB0vhaAhHQKaxHCpm29d1fZQoaAZHQG8oJCKJl8RoB0vJaAhHQKaxIGRFI/Z1fZQoaAZHQHMlZElVtGdoB0vMaAhHQKaxMXsPatd1fZQoaAZHQG6vfn4fwJBoB0vYaAhHQKaxc+xGDth1fZQoaAZHQHE3bhNucc5oB0v+aAhHQKaxtQeFL391fZQoaAZHQHBg8cuJ1q5oB0vWaAhHQKaxzz+3pfR1fZQoaAZHQHNWuuFHrhRoB0vIaAhHQKayCBbOeJ51fZQoaAZHQHJa0n9ehPFoB0vjaAhHQKaySMcZLqV1fZQoaAZHQHH24P5HmRxoB0vpaAhHQKayeN7SiM51fZQoaAZHQGjdSZKFqSJoB03oA2gIR0Cmspe40/GEdX2UKGgGR0Bx9VQhwEQoaAdL42gIR0CmsqugpSaWdX2UKGgGR0Bxi+KO1fE5aAdL7WgIR0CmsrwXQ+lkdX2UKGgGR0Bwo7DiwSrYaAdL42gIR0Cmst0FB6a9dX2UKGgGR0Bx6uuGKyfMaAdLw2gIR0CmszQPiDNAdX2UKGgGR0Bw1GJ3xFy8aAdL5mgIR0Cms5fNiYsvdX2UKGgGR0Bxc6IDYAbRaAdLx2gIR0Cms6WEsasIdX2UKGgGR0BxKakep4r0aAdLzGgIR0Cms7OVgQYldX2UKGgGR0BxNViDujREaAdL7WgIR0CmtArf+CK8dX2UKGgGR0BwJ8xBVuJlaAdL7GgIR0CmtDZbILgGdX2UKGgGR0ByOMpTdcjaaAdL5WgIR0CmtFzOgQHzdX2UKGgGR0BtpCih37k5aAdL3mgIR0CmtIHwgDA8dX2UKGgGR0BwtTpMYdhiaAdL3GgIR0CmtJKkl/pddX2UKGgGR0ByvMOLBKtgaAdLz2gIR0CmtJhf0EowdX2UKGgGR0BxTSh37k4naAdL42gIR0CmtQSNwR5DdX2UKGgGR0ByEFaq0dBCaAdL0GgIR0CmtRN7KJVKdX2UKGgGR0ByYgnndO6/aAdLzWgIR0CmtR7aRISUdX2UKGgGR0BwRijWTX8PaAdL32gIR0CmtSTiCJ40dX2UKGgGR0BxzT9MsYl6aAdL1GgIR0CmtWLsByS3dX2UKGgGR0ByAPWI42jxaAdL7WgIR0CmtYPqLS/kdX2UKGgGR0BzPBWo3rD7aAdL32gIR0CmtdZ0jkdWdX2UKGgGR0Bx08vFm4AkaAdLw2gIR0Cmtd/Qa72+dX2UKGgGR0BxFlCw8nuzaAdL8GgIR0Cmtnied07sdX2UKGgGR0BxIzDaXa8IaAdL2GgIR0CmtomgJ1JUdX2UKGgGR0ByYcGRmseXaAdL2WgIR0CmtsGcFyJbdX2UKGgGR0BzMEm4RVZLaAdNDQFoCEdAprcG7cwg1XV9lChoBkdAcMXMF2V3U2gHS+doCEdAprdBe3QUpXV9lChoBkdAcO1Tkhib2GgHS9ZoCEdAprdL6ciGFnV9lChoBkdAcYBWKMvRJGgHS/NoCEdAprfHrOZ9eHV9lChoBkdAc2c0iQkonmgHS8loCEdAprfvBSDRMXV9lChoBkdAc2l70nPVu2gHTQIBaAhHQKa39FFUhmp1fZQoaAZHQHGEfUaya/hoB0vYaAhHQKa4PyU9pyp1fZQoaAZHQHBqUzO5avBoB0vmaAhHQKa4UZlWfbt1fZQoaAZHQG5xuieumrNoB0vjaAhHQKa4Wal1r7B1fZQoaAZHQHBQ71/Ue+5oB0vEaAhHQKa4gtJ4B3l1fZQoaAZHQHIu464lQdloB0vlaAhHQKa4z2i+L3t1fZQoaAZHQHNUdfG+9J1oB0vbaAhHQKa5UmVqveR1fZQoaAZHQHEdcfNiYsxoB0vvaAhHQKa5wwxnFpB1fZQoaAZHQHFpPg3tKI1oB0vTaAhHQKa6IUB4lhR1fZQoaAZHQHHLrq6e5FxoB0vgaAhHQKa6eOOKfnR1fZQoaAZHQG2JAJC0F8poB0vkaAhHQKa7E6DoQnR1fZQoaAZHQHNHwmeDnNhoB0vZaAhHQKa7G0+C9RJ1fZQoaAZHQHJFUbtJFspoB0v9aAhHQKa7SlrM1TB1fZQoaAZHQHNa0y57PY5oB0vNaAhHQKa7k5S3sol1ZS4="
     },
     "ep_success_buffer": {
         ":type:": "<class 'collections.deque'>",
         ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
     },
-    "_n_updates": 248,
+    "_n_updates": 736,
     "observation_space": {
         ":type:": "<class 'gymnasium.spaces.box.Box'>",
         ":serialized:": "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",

ppo-LunarLander-v2/policy.optimizer.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:0036e0bcb91d734dd35ec6b5ce85eb1980ea9dc67cbbf2b280814a75822de8ae
+oid sha256:fe76bf733b24970b7550535eaa7ee1202c86f5d50b0f0881ec0c1123e32b9da2
 size 87929

ppo-LunarLander-v2/policy.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:c4853f2ab354a8f266343ffd9654596ad3788df7ecd1098e36b1a3606fc883da
+oid sha256:bf1a34e7fdacd1284c4515b4b74bd7b4242e9e16ac17d1a2820b336e8a8296e8
 size 43329

results.json

@@ -1 +1 @@
-{"mean_reward": 221.81032770619268, "std_reward": 74.95836378227389, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-05-31T02:34:08.853813"}
+{"mean_reward": 287.94081921061576, "std_reward": 14.228566865575853, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-05-31T19:19:42.385956"}