PPO for LunarLander-v2 trained agent, first test

.gitattributes

@@ -25,3 +25,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zstandard filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+*.mp4 filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,28 @@
+---
+library_name: stable-baselines3
+tags:
+- LunarLander-v2
+- deep-reinforcement-learning
+- reinforcement-learning
+- stable-baselines3
+model-index:
+- name: PPO
+  results:
+  - metrics:
+    - type: mean_reward
+      value: 204.00 +/- 16.41
+      name: mean_reward
+    task:
+      type: reinforcement-learning
+      name: reinforcement-learning
+    dataset:
+      name: LunarLander-v2
+      type: LunarLander-v2
+---
+
+  # **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
+  

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 sde_net_arch: Network architecture for extracting features\n        when using gSDE. 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 0x7f025d29c170>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f025d29c200>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f025d29c290>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f025d29c320>", "_build": "<function ActorCriticPolicy._build at 0x7f025d29c3b0>", "forward": "<function ActorCriticPolicy.forward at 0x7f025d29c440>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f025d29c4d0>", "_predict": "<function ActorCriticPolicy._predict at 0x7f025d29c560>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f025d29c5f0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f025d29c680>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f025d29c710>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f025d2d7e70>"}, "verbose": 1, "policy_kwargs": {}, "observation_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "_shape": [8], "low": "[-inf -inf -inf -inf -inf -inf -inf -inf]", "high": "[inf inf inf inf inf inf inf inf]", "bounded_below": "[False False False False False False False False]", "bounded_above": "[False False False False False False False False]", "_np_random": null}, "action_space": {":type:": "<class 'gym.spaces.discrete.Discrete'>", ":serialized:": "gAWVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu", "n": 4, "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "num_timesteps": 507904, "_total_timesteps": 500000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1651951763.8160717, "learning_rate": 0.0003, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_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, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVehAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMI/14KD5pJMECUhpRSlIwBbJRL84wBdJRHQJ8UGRxLkCF1fZQoaAZoCWgPQwiLGeHtQRpgQJSGlFKUaBVN6ANoFkdAnxlldPci4nV9lChoBmgJaA9DCAR1yqMbTV1AlIaUUpRoFU3oA2gWR0CfGiFc6eXidX2UKGgGaAloD0MIjDGwjuO0WkCUhpRSlGgVTegDaBZHQJ8bXqW1MM91fZQoaAZoCWgPQwh381SH3ENXQJSGlFKUaBVN6ANoFkdAnyOtdmg8KXV9lChoBmgJaA9DCBJr8SkALEBAlIaUUpRoFU3oA2gWR0CfJdY+Sr5qdX2UKGgGaAloD0MIDrxa7sweV0CUhpRSlGgVTegDaBZHQJ82afNA1Nx1fZQoaAZoCWgPQwjt0/GYAeViQJSGlFKUaBVN6ANoFkdAnzykZeiSJXV9lChoBmgJaA9DCIl9AijGGGBAlIaUUpRoFU3oA2gWR0CfQHFQVKwqdX2UKGgGaAloD0MIcTlegej9O0CUhpRSlGgVS7RoFkdAn0Xc/t6X0HV9lChoBmgJaA9DCIbj+QyoNwNAlIaUUpRoFU3oA2gWR0CfSURG+bmVdX2UKGgGaAloD0MIbTzYYjcBYECUhpRSlGgVTegDaBZHQJ9LfCtRvWJ1fZQoaAZoCWgPQwiILqhvmdRcQJSGlFKUaBVN6ANoFkdAn3L9w3o9tHV9lChoBmgJaA9DCAu3fCQlm0lAlIaUUpRoFU3oA2gWR0Cfc9vAXVLBdX2UKGgGaAloD0MIYYpyafz8TkCUhpRSlGgVTegDaBZHQJ9+UIQe3hJ1fZQoaAZoCWgPQwg2O1J950NfQJSGlFKUaBVN6ANoFkdAn37ycslLOHV9lChoBmgJaA9DCAVqMXiYuVlAlIaUUpRoFU3oA2gWR0CfgEa11GLDdX2UKGgGaAloD0MISpuqe2TgVUCUhpRSlGgVTegDaBZHQJ+Cd5Pdl/Z1fZQoaAZoCWgPQwgiG0gXm2xWQJSGlFKUaBVN6ANoFkdAn4hnYtg8bXV9lChoBmgJaA9DCKuvrgrU8F1AlIaUUpRoFU3oA2gWR0CfiTp1A7gbdX2UKGgGaAloD0MIAtaqXRM6KkCUhpRSlGgVTegDaBZHQJ+Kn/T9bX91fZQoaAZoCWgPQwhMb38uGjFbQJSGlFKUaBVN6ANoFkdAn5OaXF98Z3V9lChoBmgJaA9DCNp1b0ViVlFAlIaUUpRoFU3oA2gWR0CflfFG5MDfdX2UKGgGaAloD0MIDrxa7szsWUCUhpRSlGgVTegDaBZHQJ+vp2ki2Ul1fZQoaAZoCWgPQwj8j0yHTnlOQJSGlFKUaBVN6ANoFkdAn7QReC04R3V9lChoBmgJaA9DCHEC02ndbFtAlIaUUpRoFU3oA2gWR0CfulQbMotudX2UKGgGaAloD0MInRA66BL2Y0CUhpRSlGgVTegDaBZHQJ++FcKPXCl1fZQoaAZoCWgPQwheY5eoXphhQJSGlFKUaBVN6ANoFkdAn8BkjkdWAHV9lChoBmgJaA9DCIsaTMPwwllAlIaUUpRoFU3oA2gWR0Cf6QGp++dtdX2UKGgGaAloD0MIGZEotCxwZECUhpRSlGgVTegDaBZHQJ/p5/nW8RN1fZQoaAZoCWgPQwh33PC76c4nQJSGlFKUaBVLtGgWR0Cf6xz/p+tsdX2UKGgGaAloD0MIrIxGPq/aX0CUhpRSlGgVTegDaBZHQJ/0W8Gs3hp1fZQoaAZoCWgPQwgRNdHno4BUQJSGlFKUaBVN6ANoFkdAn/TxmTTvzHV9lChoBmgJaA9DCJs7+l8u1GBAlIaUUpRoFU3oA2gWR0Cf9is5GSZCdX2UKGgGaAloD0MI4rA08KN4XECUhpRSlGgVTegDaBZHQJ/3tBBzFMt1fZQoaAZoCWgPQwgAjdKl/7dhQJSGlFKUaBVN6ANoFkdAn/0ZAyEcsHV9lChoBmgJaA9DCIJvmj67J2JAlIaUUpRoFU3oA2gWR0Cf/dr8R+SbdX2UKGgGaAloD0MICYm0jT8vWkCUhpRSlGgVTegDaBZHQJ//IYgq3E11fZQoaAZoCWgPQwh+qZ83FWVjQJSGlFKUaBVN6ANoFkdAoAOhE+gUUXV9lChoBmgJaA9DCML3/gbtUF5AlIaUUpRoFU3oA2gWR0CgBKHA6+36dX2UKGgGaAloD0MIycwFLo8JNsCUhpRSlGgVS/toFkdAoAfiRSxZ+3V9lChoBmgJaA9DCDkLe9rhczBAlIaUUpRoFU0YAWgWR0CgD27SqlxfdX2UKGgGaAloD0MIMh8Q6MyQYUCUhpRSlGgVTegDaBZHQKAPsskpqh11fZQoaAZoCWgPQwgxsmSO5RVaQJSGlFKUaBVN6ANoFkdAoBF/L3bmEHV9lChoBmgJaA9DCOf/VUeOGGFAlIaUUpRoFU3oA2gWR0CgFZQxWT5gdX2UKGgGaAloD0MIePATB1D5YECUhpRSlGgVTegDaBZHQKAWjbkfcN91fZQoaAZoCWgPQwjkv0AQINBYQJSGlFKUaBVN6ANoFkdAoBngToMa0nV9lChoBmgJaA9DCLpKd9fZX1pAlIaUUpRoFU3oA2gWR0CgGk482aUidX2UKGgGaAloD0MIF/VJ7jCdYkCUhpRSlGgVTegDaBZHQKArVwRXfZV1fZQoaAZoCWgPQwjAzeLFQvVgQJSGlFKUaBVN6ANoFkdAoC9xA2Q4j3V9lChoBmgJaA9DCEzfawgOT2RAlIaUUpRoFU3oA2gWR0CgL7S4OMESdX2UKGgGaAloD0MIPWNfsvFmXUCUhpRSlGgVTegDaBZHQKAwPGYrrgR1fZQoaAZoCWgPQwgbZmg8ETFcQJSGlFKUaBVN6ANoFkdAoDD1DD0lJHV9lChoBmgJaA9DCPZcpibBclRAlIaUUpRoFU3oA2gWR0CgM2wr1/UfdX2UKGgGaAloD0MIGJP+XopXZUCUhpRSlGgVTegDaBZHQKAzxyCnP3V1fZQoaAZoCWgPQwgJNNjUefBiQJSGlFKUaBVN6ANoFkdAoDi0VHnU2HV9lChoBmgJaA9DCAfRWtHmHF9AlIaUUpRoFU3oA2gWR0CgPYM9B8hLdX2UKGgGaAloD0MIPBIvT+ctW0CUhpRSlGgVTegDaBZHQKBF1NmlImR1fZQoaAZoCWgPQwha9iSwOdJYQJSGlFKUaBVN6ANoFkdAoEYhP/JeV3V9lChoBmgJaA9DCI1jJHuE4ltAlIaUUpRoFU3oA2gWR0CgSCbXg9/0dX2UKGgGaAloD0MIb2OzI9WdVECUhpRSlGgVTegDaBZHQKBM1ywOe8R1fZQoaAZoCWgPQwiX/brTncxZQJSGlFKUaBVN6ANoFkdAoE4IP07KaHV9lChoBmgJaA9DCAkbnl4pulxAlIaUUpRoFU3oA2gWR0CgUZ16Vt4zdX2UKGgGaAloD0MIUDblCu8pXECUhpRSlGgVTegDaBZHQKBSDeEZiux1fZQoaAZoCWgPQwjp8Xub/pFWQJSGlFKUaBVN6ANoFkdAoFKtZRsMzHV9lChoBmgJaA9DCFJIMqt3I1xAlIaUUpRoFU3oA2gWR0CgZyE8ifQKdX2UKGgGaAloD0MIwCZr1EMmRUCUhpRSlGgVTegDaBZHQKBnYL/CIk91fZQoaAZoCWgPQwg3ixcLw1pgQJSGlFKUaBVN6ANoFkdAoGftFa0Qb3V9lChoBmgJaA9DCPay7bQ1ZEhAlIaUUpRoFU3oA2gWR0CgaKdytFKDdX2UKGgGaAloD0MIjBNf7SjMZECUhpRSlGgVTegDaBZHQKBrCNS619h1fZQoaAZoCWgPQwikjSPWYn5kQJSGlFKUaBVN6ANoFkdAoGtiEWZZ0XV9lChoBmgJaA9DCFx2iH/YAhhAlIaUUpRoFU0OAWgWR0Cgb/cs+V1PdX2UKGgGaAloD0MI7UeKyLC2XkCUhpRSlGgVTegDaBZHQKBwJZJ04ip1fZQoaAZoCWgPQwhZayi1lzJjQJSGlFKUaBVN6ANoFkdAoHSjMibDuXV9lChoBmgJaA9DCKxT5XtGaVZAlIaUUpRoFU3oA2gWR0Cge/sr3CbddX2UKGgGaAloD0MIrdo1Ia3TXkCUhpRSlGgVTegDaBZHQKB8OXdCVr11fZQoaAZoCWgPQwh0KENVTP5hQJSGlFKUaBVN6ANoFkdAoH3ide6ZpnV9lChoBmgJaA9DCAezCTAsYWFAlIaUUpRoFU3oA2gWR0CggexzaK1pdX2UKGgGaAloD0MIgH7fv3lFWkCUhpRSlGgVTegDaBZHQKCC5aRp1zR1fZQoaAZoCWgPQwib5bLROehiQJSGlFKUaBVN6ANoFkdAoIYmM0gr6XV9lChoBmgJaA9DCHP0+L1N91pAlIaUUpRoFU3oA2gWR0Cgho8Hv+fidX2UKGgGaAloD0MIPSr+74gUYECUhpRSlGgVTegDaBZHQKCHKPNmlIp1fZQoaAZoCWgPQwh1H4DUJoxgQJSGlFKUaBVN6ANoFkdAoJt00pEx7HV9lChoBmgJaA9DCIwrLo7KrmJAlIaUUpRoFU3oA2gWR0CgnEskhRqHdX2UKGgGaAloD0MIA8x8Bz9IXkCUhpRSlGgVTegDaBZHQKCdHSaVlf91fZQoaAZoCWgPQwg9fQT+8HMMwJSGlFKUaBVL6mgWR0Cgn58mrsBydX2UKGgGaAloD0MIKxIT1PBlXECUhpRSlGgVTegDaBZHQKCfyLiuMdd1fZQoaAZoCWgPQwj/If32daBLQJSGlFKUaBVN6ANoFkdAoKAo3rD633V9lChoBmgJaA9DCD7PnzaqPWRAlIaUUpRoFU3oA2gWR0CgpOQF9roGdX2UKGgGaAloD0MIjUY+r3iHYUCUhpRSlGgVTegDaBZHQKClFcRDkU91fZQoaAZoCWgPQwivd3+8V70XwJSGlFKUaBVL/mgWR0CgqGjlo11odX2UKGgGaAloD0MIjfFh9rK0WkCUhpRSlGgVTegDaBZHQKCprTyauwJ1fZQoaAZoCWgPQwj186YiFRRYQJSGlFKUaBVN6ANoFkdAoLEDQVsUI3V9lChoBmgJaA9DCPYpx2RxUGRAlIaUUpRoFU3oA2gWR0CgsUWfseGPdX2UKGgGaAloD0MIw5ygTQ45XECUhpRSlGgVTegDaBZHQKCzEHxjJ+51fZQoaAZoCWgPQwiygAncuuJmQJSGlFKUaBVNIwNoFkdAoLRJJNCZ4XV9lChoBmgJaA9DCDwzwXCuOFBAlIaUUpRoFU3oA2gWR0Cgt0WsaKk3dX2UKGgGaAloD0MI6USCqWbZW0CUhpRSlGgVTegDaBZHQKC4RKcNH6N1fZQoaAZoCWgPQwiYMJqV7bBiQJSGlFKUaBVN6ANoFkdAoLu3LA57xHV9lChoBmgJaA9DCBKkUuxoSkFAlIaUUpRoFUvhaBZHQKC9OwxnFpB1ZS4="}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 155, "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": 5, "clip_range": {":type:": "<class 'function'>", ":serialized:": "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"}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "system_info": {"OS": "Linux-5.4.188+-x86_64-with-Ubuntu-18.04-bionic #1 SMP Sun Apr 24 10:03:06 PDT 2022", "Python": "3.7.13", "Stable-Baselines3": "1.5.0", "PyTorch": "1.11.0+cu113", "GPU Enabled": "True", "Numpy": "1.21.6", "Gym": "0.21.0"}}

ppo-LunarLander-v2.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:90ad144712141e93871e726f415e21f37d6a35e3a19a2af51a800141b677586a
+size 144040

ppo-LunarLander-v2/_stable_baselines3_version

@@ -0,0 +1 @@
+1.5.0

ppo-LunarLander-v2/data

@@ -0,0 +1,94 @@
+{
+    "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 sde_net_arch: Network architecture for extracting features\n        when using gSDE. 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 0x7f025d29c170>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f025d29c200>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f025d29c290>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f025d29c320>",
+        "_build": "<function ActorCriticPolicy._build at 0x7f025d29c3b0>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7f025d29c440>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f025d29c4d0>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7f025d29c560>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f025d29c5f0>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f025d29c680>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f025d29c710>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc_data object at 0x7f025d2d7e70>"
+    },
+    "verbose": 1,
+    "policy_kwargs": {},
+    "observation_space": {
+        ":type:": "<class 'gym.spaces.box.Box'>",
+        ":serialized:": "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",
+        "dtype": "float32",
+        "_shape": [
+            8
+        ],
+        "low": "[-inf -inf -inf -inf -inf -inf -inf -inf]",
+        "high": "[inf inf inf inf inf inf inf inf]",
+        "bounded_below": "[False False False False False False False False]",
+        "bounded_above": "[False False False False False False False False]",
+        "_np_random": null
+    },
+    "action_space": {
+        ":type:": "<class 'gym.spaces.discrete.Discrete'>",
+        ":serialized:": "gAWVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu",
+        "n": 4,
+        "_shape": [],
+        "dtype": "int64",
+        "_np_random": null
+    },
+    "n_envs": 16,
+    "num_timesteps": 507904,
+    "_total_timesteps": 500000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1651951763.8160717,
+    "learning_rate": 0.0003,
+    "tensorboard_log": null,
+    "lr_schedule": {
+        ":type:": "<class 'function'>",
+        ":serialized:": "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"
+    },
+    "_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,
+    "ep_info_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "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"
+    },
+    "ep_success_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
+    },
+    "_n_updates": 155,
+    "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": 5,
+    "clip_range": {
+        ":type:": "<class 'function'>",
+        ":serialized:": "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"
+    },
+    "clip_range_vf": null,
+    "normalize_advantage": true,
+    "target_kl": null
+}

ppo-LunarLander-v2/policy.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:40a9e54a25fe29e1a361eb42cb93f48c7a2f93a46827698cd0a2185861304ae0
+size 84829

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b4e582c0e5bf37dbe263a09e98d0d60ff0bcec822929a3122f0fbc73fe574e72
+size 43201

ppo-LunarLander-v2/pytorch_variables.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d030ad8db708280fcae77d87e973102039acd23a11bdecc3db8eb6c0ac940ee1
+size 431

ppo-LunarLander-v2/system_info.txt

@@ -0,0 +1,7 @@
+OS: Linux-5.4.188+-x86_64-with-Ubuntu-18.04-bionic #1 SMP Sun Apr 24 10:03:06 PDT 2022
+Python: 3.7.13
+Stable-Baselines3: 1.5.0
+PyTorch: 1.11.0+cu113
+GPU Enabled: True
+Numpy: 1.21.6
+Gym: 0.21.0

replay.mp4

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:6c8f31b7d7bac385f28c64ef03f9f5ed0ea3dcd368a3d35ed5e2ec99c16df507
+size 239620

results.json

@@ -0,0 +1 @@
+{"mean_reward": 203.99509499781828, "std_reward": 16.413613949322137, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-05-07T19:48:38.096127"}