PPO LunarLander-v2 trained agent version 1

.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: 263.05 +/- 23.87
+      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 0x7f33aa57d8c0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f33aa57d950>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f33aa57d9e0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f33aa57da70>", "_build": "<function ActorCriticPolicy._build at 0x7f33aa57db00>", "forward": "<function ActorCriticPolicy.forward at 0x7f33aa57db90>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f33aa57dc20>", "_predict": "<function ActorCriticPolicy._predict at 0x7f33aa57dcb0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f33aa57dd40>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f33aa57ddd0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f33aa57de60>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f33aa5cc5a0>"}, "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": 24, "num_timesteps": 516096, "_total_timesteps": 500000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1651845777.3208268, "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:": "gAWViwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYYAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAJSMBW51bXB5lIwFZHR5cGWUk5SMAmIxlImIh5RSlChLA4wBfJROTk5K/////0r/////SwB0lGJLGIWUjAFDlHSUUpQu"}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.032192, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 336, "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": 16, "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 sha256:450de1a2443d9387ca41eb8c2f0bd6055003ef233aaf9b162ac4d2b620e80a0a
+size 144441

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 0x7f33aa57d8c0>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f33aa57d950>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f33aa57d9e0>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f33aa57da70>",
+        "_build": "<function ActorCriticPolicy._build at 0x7f33aa57db00>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7f33aa57db90>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f33aa57dc20>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7f33aa57dcb0>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f33aa57dd40>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f33aa57ddd0>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f33aa57de60>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc_data object at 0x7f33aa5cc5a0>"
+    },
+    "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": 24,
+    "num_timesteps": 516096,
+    "_total_timesteps": 500000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1651845777.3208268,
+    "learning_rate": 0.0003,
+    "tensorboard_log": null,
+    "lr_schedule": {
+        ":type:": "<class 'function'>",
+        ":serialized:": "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"
+    },
+    "_last_obs": {
+        ":type:": "<class 'numpy.ndarray'>",
+        ":serialized:": "gAWVdQMAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAwAAAAAAADOepbx7GrC6k8ksuK3PFrNaLEM65r9FNwAAgD8AAIA/TdkgvcOBULqFbaC75IS0N186ZzrUbhS3AACAPwAAgD9mKEe9KaRmuviCRLmC1XS0veQGO3KiZTgAAIA/AACAP1pTkL3DYXC6kITwu6tJYLZyMUA7cGXHNQAAgD8AAIA/AJovPKTwEDjly5S7cnc9PHAGort+e4u8AACAPwAAAAAaiCU9XCMTuqpsQbvihgG3D+9iO22YYzoAAIA/AACAP2bVnb30Gq4/0vvOvuy4t75AkcW9BiiwvQAAAAAAAAAAzfRQuw0pLT7KDV+9DgHGvoOBDT3TN9W9AAAAAAAAAADNXOM7wylOuursNzv37ao1yWs/OhNrVLoAAIA/AACAPwB5D76VKGw/v/QUvrYuBb9T2yS+SxjIvQAAAAAAAAAAzYhGvK7djbpHij+6qzivtiYIpjrS+lw5AACAPwAAgD+a75C9Hz3AuUb94DoiEzq03Yj5ufZKAboAAIA/AACAP5pb0Txcz0K65XxlujAGh7hLkSO7XoKLOQAAgD8AAIA/GjBavRTKiLquYg27IoY7PK14KLuzeCe9AACAPwAAgD+m+gU+6wydP9uSrT7qPg6/supHPsbZmTwAAAAAAAAAAM3yrDwpBFW6GL3dPM+GyLwxCx27aKGvvQAAAAAAAIA/zfBXPMOZDrr11GC6ZIr8tdVROLoN84I5AACAPwAAgD8avnm97GG4uUtjY7uKg5e5kUgZO/aciDoAAIA/AACAPxpnFj3DXXe6zS5iO80KGThomCE7WZ8BugAAgD8AAIA/mrWguylcJLqxBS065WGTtnLxpjtiro21AACAPwAAgD/NEIk7XKswuuA4aTp6LGE120u6uUHOg7kAAIA/AACAPzPKgL24Bo659pMhufzXA7QVf4y6flxBOAAAgD8AAIA/MxC9vFLw6bkoOo+7tKCmNW5r1DmwmxG1AACAPwAAgD+NAYM+NYqZPz5K3D4BsBe/zZjJPvgaGj4AAAAAAAAAAJSMBW51bXB5lIwFZHR5cGWUk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGJLGEsIhpSMAUOUdJRSlC4="
+    },
+    "_last_episode_starts": {
+        ":type:": "<class 'numpy.ndarray'>",
+        ":serialized:": "gAWViwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYYAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAJSMBW51bXB5lIwFZHR5cGWUk5SMAmIxlImIh5RSlChLA4wBfJROTk5K/////0r/////SwB0lGJLGIWUjAFDlHSUUpQu"
+    },
+    "_last_original_obs": null,
+    "_episode_num": 0,
+    "use_sde": false,
+    "sde_sample_freq": -1,
+    "_current_progress_remaining": -0.032192,
+    "ep_info_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "gAWVehAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMI0LcFS3VsYUCUhpRSlIwBbJRN6AOMAXSUR0CRhRu89Oh1dX2UKGgGaAloD0MILEfIQJ4RWUCUhpRSlGgVTegDaBZHQJGFQN0/4Zd1fZQoaAZoCWgPQwj1TC8xlkdaQJSGlFKUaBVN6ANoFkdAkYo/FefI0nV9lChoBmgJaA9DCI3PZP88pTFAlIaUUpRoFUtaaBZHQJGMeu3c5811fZQoaAZoCWgPQwiq1y0CYz9dQJSGlFKUaBVN6ANoFkdAkY9sBIWgvnV9lChoBmgJaA9DCP+Xa9ECg19AlIaUUpRoFU3oA2gWR0CRkGoPCl7/dX2UKGgGaAloD0MImmA41zCZYkCUhpRSlGgVTegDaBZHQJGSx7dBSk11fZQoaAZoCWgPQwh41QPmIQRWQJSGlFKUaBVN6ANoFkdAkZX/d/J/5XV9lChoBmgJaA9DCMrhk04k5l9AlIaUUpRoFU3oA2gWR0CRmtrp7kXDdX2UKGgGaAloD0MIXwfOGVG4WUCUhpRSlGgVTegDaBZHQJGc0i/wiJR1fZQoaAZoCWgPQwgoC19faxpgQJSGlFKUaBVN6ANoFkdAkZ90mx+rl3V9lChoBmgJaA9DCILHt3cN1FxAlIaUUpRoFU3oA2gWR0CRpYPiT+vRdX2UKGgGaAloD0MIZMvydRkoWUCUhpRSlGgVTegDaBZHQJG2jM9r4351fZQoaAZoCWgPQwgSvYxiuZtiQJSGlFKUaBVN6ANoFkdAkbmiiVSn+HV9lChoBmgJaA9DCA+4rpgRLGNAlIaUUpRoFU3oA2gWR0CRuvradtl7dX2UKGgGaAloD0MIhZUKKioqY0CUhpRSlGgVTegDaBZHQJG++YJE6T51fZQoaAZoCWgPQwjGNNO9TjRjQJSGlFKUaBVN6ANoFkdAkdyxTKkl/3V9lChoBmgJaA9DCHSy1Hq/OFtAlIaUUpRoFU3oA2gWR0CR4SRUFSsKdX2UKGgGaAloD0MIlWBxOPMsXkCUhpRSlGgVTegDaBZHQJHnvBInSfF1fZQoaAZoCWgPQwj9MEJ4tBhZQJSGlFKUaBVN6ANoFkdAkes42wV0tHV9lChoBmgJaA9DCCsTfqmfL1tAlIaUUpRoFU3oA2gWR0CR8CF98Z1ndX2UKGgGaAloD0MIdVjhlg9NYECUhpRSlGgVTegDaBZHQJKbz1CgK4R1fZQoaAZoCWgPQwiLw5lfTRRiQJSGlFKUaBVN6ANoFkdAkpzB+jM3ZXV9lChoBmgJaA9DCP5l9+Rhj0lAlIaUUpRoFUulaBZHQJKeCYTj/+91fZQoaAZoCWgPQwg6W0BoPRxlQJSGlFKUaBVN6ANoFkdAkqPW5lOGkHV9lChoBmgJaA9DCM8R+S4lRWBAlIaUUpRoFU3oA2gWR0CSpZx5cC5mdX2UKGgGaAloD0MIXMZNDbRuZECUhpRSlGgVTegDaBZHQJKlv/bTMJR1fZQoaAZoCWgPQwhXk6espudRQJSGlFKUaBVLlGgWR0CSqMKP4mCzdX2UKGgGaAloD0MI4rA08KNzYUCUhpRSlGgVTegDaBZHQJKqlLXcxj91fZQoaAZoCWgPQwgxeJj2TTxhQJSGlFKUaBVN6ANoFkdAkqy+Hvc8DHV9lChoBmgJaA9DCCkhWFWvkmNAlIaUUpRoFU3oA2gWR0CSr3DdP+GXdX2UKGgGaAloD0MIcHfWbjtpZkCUhpRSlGgVTegDaBZHQJKwW7lJYkp1fZQoaAZoCWgPQwhoeR7cnRpfQJSGlFKUaBVN6ANoFkdAkrJ+stCiRHV9lChoBmgJaA9DCJQSglX1QVtAlIaUUpRoFU3oA2gWR0CStV7UXpGGdX2UKGgGaAloD0MIbToCuFntYUCUhpRSlGgVTegDaBZHQJK5bJIUahp1fZQoaAZoCWgPQwgFUIwsmaJgQJSGlFKUaBVN6ANoFkdAkrsaDK5kLHV9lChoBmgJaA9DCNGSx9Ny+2BAlIaUUpRoFU3oA2gWR0CSvUvXbuc+dX2UKGgGaAloD0MIOPbsuUw1YUCUhpRSlGgVTegDaBZHQJLCfvjOs1d1fZQoaAZoCWgPQwjkLsIU5WIWwJSGlFKUaBVLZmgWR0CSwpq7yxzJdX2UKGgGaAloD0MI6e3PRUPbW0CUhpRSlGgVTegDaBZHQJLQ9ew9q1x1fZQoaAZoCWgPQwggCft2kqJlQJSGlFKUaBVN6ANoFkdAktOD28IzFnV9lChoBmgJaA9DCDlHHR1X511AlIaUUpRoFU3oA2gWR0CS1JUrkKeDdX2UKGgGaAloD0MI7dKGw9IVXkCUhpRSlGgVTegDaBZHQJLX2HN5dGB1fZQoaAZoCWgPQwh7LlOTYEhgQJSGlFKUaBVN6ANoFkdAkvGJgkTpPnV9lChoBmgJaA9DCPpEniRd2FlAlIaUUpRoFU3oA2gWR0CS+5uLaVUudX2UKGgGaAloD0MIuXGL+bntZkCUhpRSlGgVTegDaBZHQJL+xycTakB1fZQoaAZoCWgPQwgY6UXtftdkQJSGlFKUaBVN6ANoFkdAkwhatozvZ3V9lChoBmgJaA9DCANBgAwdZ2VAlIaUUpRoFU3oA2gWR0CTq4Y2bXpXdX2UKGgGaAloD0MIwNAjRs/FW0CUhpRSlGgVTegDaBZHQJOssdyT6i11fZQoaAZoCWgPQwgEdF/O7GZiQJSGlFKUaBVN6ANoFkdAk7HfXGwRoXV9lChoBmgJaA9DCEYHJGHf1WRAlIaUUpRoFU3oA2gWR0CTs3attALRdX2UKGgGaAloD0MIx2eyf56vW0CUhpRSlGgVTegDaBZHQJOzmZOSGJx1fZQoaAZoCWgPQwh4eqUsw9hhQJSGlFKUaBVN6ANoFkdAk7Zkc0cfeXV9lChoBmgJaA9DCDUomgew0FxAlIaUUpRoFU3oA2gWR0CTt/VAzHjqdX2UKGgGaAloD0MIYWwhyMHoYECUhpRSlGgVTegDaBZHQJO5yqdYnv51fZQoaAZoCWgPQwihTKPJRQVmQJSGlFKUaBVN6ANoFkdAk7wngYP5HnV9lChoBmgJaA9DCNicg2fC72ZAlIaUUpRoFU3oA2gWR0CTvPDXvphXdX2UKGgGaAloD0MIQbgCCnXyY0CUhpRSlGgVTegDaBZHQJO+2tDD0lJ1fZQoaAZoCWgPQwiFQZlGE9dhQJSGlFKUaBVN6ANoFkdAk8GJ2dNFjXV9lChoBmgJaA9DCCAot+17lWNAlIaUUpRoFU3oA2gWR0CTxz8PFvQ4dX2UKGgGaAloD0MIqBq9GqCSZECUhpRSlGgVTegDaBZHQJPJcpH7P6d1fZQoaAZoCWgPQwhNFYxK6nJJQJSGlFKUaBVLimgWR0CTywAIY3vQdX2UKGgGaAloD0MIIxKFlvVJYECUhpRSlGgVTegDaBZHQJPOk+A3DN11fZQoaAZoCWgPQwgc0T3rGlNeQJSGlFKUaBVN6ANoFkdAk86s4YJmd3V9lChoBmgJaA9DCCum0k84qFxAlIaUUpRoFU3oA2gWR0CT3HCP6sQvdX2UKGgGaAloD0MISKgZUkWoYUCUhpRSlGgVTegDaBZHQJPe7JlrdnF1fZQoaAZoCWgPQwg10HzO3cFfQJSGlFKUaBVN6ANoFkdAk+AZa7mMfnV9lChoBmgJaA9DCOHvF7MlCWJAlIaUUpRoFU3oA2gWR0CT45Ym9g4PdX2UKGgGaAloD0MIG0esxaceTkCUhpRSlGgVS5ZoFkdAk++UL2HtW3V9lChoBmgJaA9DCAjNrnsrpWVAlIaUUpRoFU3oA2gWR0CT/EOfdyksdX2UKGgGaAloD0MIrfnxl5a6YECUhpRSlGgVTegDaBZHQJQFb3Ehq0t1fZQoaAZoCWgPQwhCJEOOLX5gQJSGlFKUaBVN6ANoFkdAlAhh/3Fkx3V9lChoBmgJaA9DCPXabKxE0GJAlIaUUpRoFU3oA2gWR0CUEQZNfw7UdX2UKGgGaAloD0MIqtVXVwWZYUCUhpRSlGgVTegDaBZHQJQR2F10T111fZQoaAZoCWgPQwir6Xqi69FbQJSGlFKUaBVN6ANoFkdAlBMEF4cFQnV9lChoBmgJaA9DCAXfNH12pWJAlIaUUpRoFU3oA2gWR0CUuy2zfJmvdX2UKGgGaAloD0MIp0BmZ1H7ZkCUhpRSlGgVTegDaBZHQJS8vlXA/LV1fZQoaAZoCWgPQwiIoGr06hljQJSGlFKUaBVN6ANoFkdAlLzbXtjTa3V9lChoBmgJaA9DCBFvnX87RmVAlIaUUpRoFU3oA2gWR0CUv42icoYvdX2UKGgGaAloD0MI6KOMuAD1ZUCUhpRSlGgVTegDaBZHQJTBDVwxWT51fZQoaAZoCWgPQwgYsU8Axe5fQJSGlFKUaBVN6ANoFkdAlMLGFnIyTXV9lChoBmgJaA9DCNxmKsSjuGNAlIaUUpRoFU3oA2gWR0CUxRO0LMLXdX2UKGgGaAloD0MIlNv2PWoSaUCUhpRSlGgVTegDaBZHQJTF2rhisn11fZQoaAZoCWgPQwiIaHQHMUxiQJSGlFKUaBVN6ANoFkdAlMpXjZL7GnV9lChoBmgJaA9DCLN78rBQbWBAlIaUUpRoFU3oA2gWR0CU0ATX8O0+dX2UKGgGaAloD0MI9N4YAgArZECUhpRSlGgVTegDaBZHQJTSQK9f1Hx1fZQoaAZoCWgPQwg0ngjivBtkQJSGlFKUaBVN6ANoFkdAlNPlJ6IFeXV9lChoBmgJaA9DCEsjZvb57WFAlIaUUpRoFU3oA2gWR0CU11It16mgdX2UKGgGaAloD0MIDeIDO35ZYkCUhpRSlGgVTegDaBZHQJTXbCFbmlt1fZQoaAZoCWgPQwjuQnOdxnNmQJSGlFKUaBVN6ANoFkdAlOTmCmMwUXV9lChoBmgJaA9DCIC21ayzVmhAlIaUUpRoFU3oA2gWR0CU50bbUPQOdX2UKGgGaAloD0MIflaZKS2uYECUhpRSlGgVTegDaBZHQJTryu9vjwR1fZQoaAZoCWgPQwhvgQTFj7NnQJSGlFKUaBVN6ANoFkdAlPfYzrNW2nV9lChoBmgJaA9DCIIAGTr2rmdAlIaUUpRoFU3oA2gWR0CVBD8R+SbIdX2UKGgGaAloD0MIO1RTknWEZkCUhpRSlGgVTegDaBZHQJUNEUSIxg11fZQoaAZoCWgPQwg0nZ0MDlJjQJSGlFKUaBVN6ANoFkdAlQ//P9kz43V9lChoBmgJaA9DCAvvchFfaGNAlIaUUpRoFU3oA2gWR0CVGGzEJjUedX2UKGgGaAloD0MIPwJ/+PkbZUCUhpRSlGgVTegDaBZHQJUZPtCzC1t1fZQoaAZoCWgPQwhhGLDkquJhQJSGlFKUaBVN6ANoFkdAlRphLbpNbnV9lChoBmgJaA9DCPQ2NjtSjT5AlIaUUpRoFUtvaBZHQJUcMUYbbUR1ZS4="
+    },
+    "ep_success_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
+    },
+    "_n_updates": 336,
+    "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": 16,
+    "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:f095a9117a06c48eefbaf1467f079bd159d480e9bd32c02a95fcb49b2c6f604c
+size 84893

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ff6f593f8da89b10c630b968efe0c3022e179014a24503d2d1aa37c14dae6e1c
+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 sha256:9846bf2b1ef60c04d645cb9ea0133e76702c924e947456869f2f737b7404775a
+size 217157

results.json

@@ -0,0 +1 @@
+{"mean_reward": 263.0465704215652, "std_reward": 23.867483669853673, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-05-06T14:42:54.524890"}