Upload PPO LunarLander-v2 trained agent

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+replay.mp4 filter=lfs diff=lfs merge=lfs -text

README.md

@@ -1,3 +1,37 @@
----
-license: mit
----
+---
+library_name: stable-baselines3
+tags:
+- LunarLander-v2
+- deep-reinforcement-learning
+- reinforcement-learning
+- stable-baselines3
+model-index:
+- name: PPO
+  results:
+  - task:
+      type: reinforcement-learning
+      name: reinforcement-learning
+    dataset:
+      name: LunarLander-v2
+      type: LunarLander-v2
+    metrics:
+    - type: mean_reward
+      value: 222.44 +/- 80.20
+      name: mean_reward
+      verified: false
+---
+
+# **PPO** Agent playing **LunarLander-v2**
+This is a trained model of a **PPO** agent playing **LunarLander-v2**
+using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
+
+## Usage (with Stable-baselines3)
+TODO: Add your code
+
+
+```python
+from stable_baselines3 import ...
+from huggingface_sb3 import load_from_hub
+
+...
+```

config.json

@@ -0,0 +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 0x7f7e0457bba0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f7e0457bc40>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f7e0457bce0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f7e0457bd80>", "_build": "<function ActorCriticPolicy._build at 0x7f7e0457be20>", "forward": "<function ActorCriticPolicy.forward at 0x7f7e0457bec0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f7e0457bf60>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f7e04588040>", "_predict": "<function ActorCriticPolicy._predict at 0x7f7e045880e0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f7e04588180>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f7e04588220>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f7e045882c0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f7e04518dc0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1752563572836109260, "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:": "gAWVhAAAAAAAAACME251bXB5Ll9jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksQhZSMAUOUdJRSlC4="}, "_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:": "gAWV/gsAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpRHQHGAfiT+vQqMAWyUS/qMAXSUR0CZus9IwudxdX2UKGgGR0BwybS5RTCMaAdL9mgIR0CZvPQGfPHDdX2UKGgGR0BxbsvUSZjQaAdNFgFoCEdAmb032ZiNKnV9lChoBkdAblznlGPPs2gHS+1oCEdAmb3u+qR2bHV9lChoBkdAcoqsCT2WZGgHTQcBaAhHQJm+UIu5BkZ1fZQoaAZHQHGIwJkXk5poB00tAWgIR0CZvwm2b5M2dX2UKGgGR0BydiE6DGtIaAdL5GgIR0CZv2BQvYe1dX2UKGgGR0Bw/PdRBNVSaAdLxWgIR0CZv11R+BpYdX2UKGgGR0ByODSy+pOvaAdL7GgIR0CZv61A7gbZdX2UKGgGR0BzmFZntfG/aAdLwGgIR0CZv63QD3dsdX2UKGgGR0BwlL2IwdsBaAdNDgFoCEdAmcA9pudf9nV9lChoBkdAceZoX9BKMGgHTREBaAhHQJnAYi1RceN1fZQoaAZHQHER1wHZ9NNoB0vfaAhHQJnBcI1LrX11fZQoaAZHQG7mr8zhxYJoB0v4aAhHQJnCa2w3YL91fZQoaAZHQG+mPwuuiexoB0vGaAhHQJnDLSXt0FN1fZQoaAZHQG86EI5YHPhoB0vLaAhHQJnEQjW07bN1fZQoaAZHQHB5qUFB6a9oB0v/aAhHQJnFXmOlwcZ1fZQoaAZHQHG9CdvsJIFoB0upaAhHQJnFy+yquKZ1fZQoaAZHQHAcx+WnjyZoB0vEaAhHQJnF8ImgJ1J1fZQoaAZHQHLFttqHoHNoB0vhaAhHQJnGoJD3M6l1fZQoaAZHQHG5OAEt/WloB00GAWgIR0CZxtK9PDYRdX2UKGgGR0Bt3+ecx0uEaAdL62gIR0CZxvYUWVNYdX2UKGgGR0BytUWM0gr6aAdL+GgIR0CZxxCU5dWydX2UKGgGR0BxwuXZ5AyEaAdN7wFoCEdAmceazu4PPXV9lChoBkdAceSpY9xIa2gHS/toCEdAmceztTkyUXV9lChoBkdAch90+1SflWgHS/ZoCEdAmcgJeeFtbnV9lChoBkdAY2GEbHZK4GgHTegDaAhHQJnJoCgbp/x1fZQoaAZHQHNMC9M9KVZoB00UAWgIR0CZygXtBv74dX2UKGgGR0Bwz1MpPRAsaAdLxmgIR0CZy7RISUTtdX2UKGgGR0BtmxCngpBpaAdLvGgIR0CZzAlWwNb1dX2UKGgGR0BwV7HMlkYoaAdL4GgIR0CZzYyy2QXAdX2UKGgGR0BvjOLP2PDHaAdLyGgIR0CZzbGQjlgddX2UKGgGR0BxbkqUeMhpaAdLy2gIR0CZzgbQkX1rdX2UKGgGR0Bwf6K4x1xLaAdNBwFoCEdAmc4XNorWiHV9lChoBkdAY62zHjp9qmgHTegDaAhHQJnOv3Ehq0t1fZQoaAZHQHHKnm3fAKxoB00oAWgIR0CZzyi9qUNbdX2UKGgGR0Bt5hOJtSAIaAdL12gIR0CZz0CAMDwIdX2UKGgGR0BtSypJf6XTaAdNUgFoCEdAmc+VF2FFlXV9lChoBkdAcbA24/eLvWgHTQkBaAhHQJnPqXmeUY91fZQoaAZHQHGg3Vsk6cRoB00JAWgIR0CZz8Xd0q6OdX2UKGgGR0BxE+ml67d0aAdL02gIR0CZ0aZx7zCldX2UKGgGR0BwBW06YE4eaAdL0GgIR0CZ0+n5SFXadX2UKGgGR0BxV+1eBxxUaAdLy2gIR0CZ1u6Mir1edX2UKGgGR0Bw83mxMWXUaAdNAgFoCEdAmdchd+ocaXV9lChoBkdAcYNYg7o0RGgHS9ZoCEdAmdcwOjIq9XV9lChoBkdAb/NP+n62v2gHS9FoCEdAmdc9IClrM3V9lChoBkdASstlum78N2gHS79oCEdAmde+mBOHnHV9lChoBkdAc1MaVD8cdmgHS9doCEdAmdgvA44p+nV9lChoBkdAcQix8D0UXmgHS9hoCEdAmdhIiX6ZY3V9lChoBkdAcCvmZVn27GgHS81oCEdAmdheIdlunHV9lChoBkdAcp7mMOwxFmgHS+9oCEdAmdig3tKIznV9lChoBkdAcm5SG8EmpmgHTRMBaAhHQJnZBULlV951fZQoaAZHQHC58AzYVZdoB0v1aAhHQJnZdVMmF8J1fZQoaAZHQHBPH84xUNtoB0vsaAhHQJna0NXo1UF1fZQoaAZHQG4z8cuJ1q5oB0vZaAhHQJnb5HG0eEJ1fZQoaAZHQG0LAS39aU1oB0vOaAhHQJndewTufEp1fZQoaAZHQG+PHEVFhG9oB0vYaAhHQJndtmcvugJ1fZQoaAZHQEA+ezUqhDhoB0vWaAhHQJndzu6VdHF1fZQoaAZHQG6D7aRISUVoB0u8aAhHQJneAe0Xxe91fZQoaAZHQHKDyk9ECvJoB0vUaAhHQJnfRvBJqZd1fZQoaAZHQHMmL3bmEGtoB0vkaAhHQJnfU5yU9p11fZQoaAZHQHOTtOZb6gxoB00IAWgIR0CZ33yPuG9IdX2UKGgGR0BygfV7Qb++aAdL5mgIR0CZ35LUTcqOdX2UKGgGR0Bvyt6Rhc7haAdL6GgIR0CZ4Et29tdidX2UKGgGR0BwDzEzfrKOaAdL9mgIR0CZ4S0BwMpgdX2UKGgGR0BurL3dsSCfaAdL1GgIR0CZ4aD5j6N3dX2UKGgGR0Bt2ntx+8XfaAdL1GgIR0CZ5O1LamGedX2UKGgGR0BjHRvBJqZdaAdN6ANoCEdAmeUq8lHBlHV9lChoBkdAcq805lvqDGgHS9loCEdAmeVAvpQk5nV9lChoBkdAcOajmSyMUGgHS7poCEdAmeX3V5KODXV9lChoBkdAYl7WXkYGdWgHTegDaAhHQJnmCPikwex1fZQoaAZHQHA8zQ3PzFxoB0v8aAhHQJnmKaF23a11fZQoaAZHQHGE2CROk+JoB006AWgIR0CZ5pbWmP5pdX2UKGgGR0BuzarWAf+1aAdL3WgIR0CZ5tjGkvbodX2UKGgGR0ByAwlTm4iHaAdLtWgIR0CZ5/jz7MxHdX2UKGgGR0BvNbhP0qYraAdL02gIR0CZ6HjLSuyNdX2UKGgGR0BwkwDeTFERaAdNsgFoCEdAme1JEH+qBHV9lChoBkdAcKaaCL/CImgHTY8BaAhHQJntVECvHLl1fZQoaAZHQGKISRKYiPhoB03oA2gIR0CZ7ZNNahYedX2UKGgGR0BxDHaIvalDaAdL7WgIR0CZ7cOeJ53UdX2UKGgGR0BwLl2GIsRQaAdLyWgIR0CZ7fLA57w8dX2UKGgGR0BxNzyEtdzGaAdL5GgIR0CZ7jUedTYNdX2UKGgGR0BzBUq7ROUMaAdNAQFoCEdAme49+CsfaHV9lChoBkdAcWUJ3PiT+2gHS/toCEdAme5K9CeEqXV9lChoBkdAcFFcCo0hvGgHS/FoCEdAme6h+vyLAHV9lChoBkdAcYz2sq8UVWgHTQQBaAhHQJnvSiblRxd1fZQoaAZHQG9e5AhStNloB00CAWgIR0CZ7+Tzd1uBdX2UKGgGR0BwtxtelbeNaAdL/mgIR0CZ8MBD5TIedX2UKGgGR0ByCKlwcYIjaAdNFAFoCEdAmfHZQcghbHV9lChoBkdAcVvRgqmTDGgHS8toCEdAmfNzCtRvWHV9lChoBkdAcQ7YzzmOl2gHS8FoCEdAmfP+lCTlk3V9lChoBkdAcrxYaYNRWWgHS9ZoCEdAmfQLh3qzJXV9lChoBkdAQ9SwljVhC2gHS9VoCEdAmfQrHhjvu3V9lChoBkdAcMrrFwT/Q2gHS9poCEdAmfR7kn1FpnV9lChoBkdAcBSNUfgaWGgHS+NoCEdAmfUGK/EfknV9lChoBkdAbXLiVjZtemgHS+VoCEdAmfUuaOPvKHV9lChoBkdAcfahg3Lmp2gHS9VoCEdAmfdechC+lHV9lChoBkdAb61AgxJumGgHS/xoCEdAmfeiH/Lkj3V9lChoBkdAY9d6k690zWgHTegDaAhHQJn4l6Ww/xF1fZQoaAZHQG1W3uVopQVoB01YAWgIR0CZ+jS5iExqdWUu"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 310, "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:": "gAWV3AAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFm51bXB5Ll9jb3JlLm11bHRpYXJyYXmUjAZzY2FsYXKUk5SMBW51bXB5lIwFZHR5cGWUk5SMAmk4lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGJDCAQAAAAAAAAAlIaUUpSMBXN0YXJ0lGgIaA5DCAAAAAAAAAAAlIaUUpSMBl9zaGFwZZQpjAVkdHlwZZRoDowKX25wX3JhbmRvbZROdWIu", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "n_steps": 2048, "gamma": 0.99, "gae_lambda": 0.95, "ent_coef": 0.0, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 64, "n_epochs": 10, "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-6.1.123+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sun Mar 30 16:01:29 UTC 2025", "Python": "3.11.13", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.6.0+cu124", "GPU Enabled": "True", "Numpy": "2.0.2", "Cloudpickle": "3.1.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}

ppo-LunarLander-v2.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:8a8b2b86a528784b5e4127158c5220cd20f25353b4a601e56f24c4c2dda8ad8e
+size 148039

ppo-LunarLander-v2/_stable_baselines3_version

@@ -0,0 +1 @@
+2.0.0a5

ppo-LunarLander-v2/data

@@ -0,0 +1,99 @@
+{
+    "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 0x7f7e0457bba0>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f7e0457bc40>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f7e0457bce0>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f7e0457bd80>",
+        "_build": "<function ActorCriticPolicy._build at 0x7f7e0457be20>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7f7e0457bec0>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f7e0457bf60>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f7e04588040>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7f7e045880e0>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f7e04588180>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f7e04588220>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f7e045882c0>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x7f7e04518dc0>"
+    },
+    "verbose": 1,
+    "policy_kwargs": {},
+    "num_timesteps": 1015808,
+    "_total_timesteps": 1000000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1752563572836109260,
+    "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:": "gAWVhAAAAAAAAACME251bXB5Ll9jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksQhZSMAUOUdJRSlC4="
+    },
+    "_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": 310,
+    "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:": "gAWV3AAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFm51bXB5Ll9jb3JlLm11bHRpYXJyYXmUjAZzY2FsYXKUk5SMBW51bXB5lIwFZHR5cGWUk5SMAmk4lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGJDCAQAAAAAAAAAlIaUUpSMBXN0YXJ0lGgIaA5DCAAAAAAAAAAAlIaUUpSMBl9zaGFwZZQpjAVkdHlwZZRoDowKX25wX3JhbmRvbZROdWIu",
+        "n": "4",
+        "start": "0",
+        "_shape": [],
+        "dtype": "int64",
+        "_np_random": null
+    },
+    "n_envs": 16,
+    "n_steps": 2048,
+    "gamma": 0.99,
+    "gae_lambda": 0.95,
+    "ent_coef": 0.0,
+    "vf_coef": 0.5,
+    "max_grad_norm": 0.5,
+    "batch_size": 64,
+    "n_epochs": 10,
+    "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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"
+    }
+}

ppo-LunarLander-v2/policy.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a15ce215db71a66e30190b86e65663f0696d987e00ecafe01b821be80ec7ba42
+size 88362

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b265eae9d0dabaa26ff5e50df1d7a993042e7ffd553b0f6eec078576634788b2
+size 43762

ppo-LunarLander-v2/pytorch_variables.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0c35cea3b2e60fb5e7e162d3592df775cd400e575a31c72f359fb9e654ab00c5
+size 864

ppo-LunarLander-v2/system_info.txt

@@ -0,0 +1,9 @@
+- OS: Linux-6.1.123+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sun Mar 30 16:01:29 UTC 2025
+- Python: 3.11.13
+- Stable-Baselines3: 2.0.0a5
+- PyTorch: 2.6.0+cu124
+- GPU Enabled: True
+- Numpy: 2.0.2
+- Cloudpickle: 3.1.1
+- Gymnasium: 0.28.1
+- OpenAI Gym: 0.25.2

replay.mp4

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:aa0ec74791e19cf82e4f428dd7f2148aa0d08e6dd53860eb68799f8fa2219a9f
+size 156490

results.json

@@ -0,0 +1 @@
+{"mean_reward": 222.4446372484421, "std_reward": 80.19845127559584, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2025-07-15T07:58:58.549024"}