tomascufaro commited on
Commit
b9a6d98
·
1 Parent(s): 75d9f71

first lunalander

Browse files
.gitattributes CHANGED
@@ -25,3 +25,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
25
  *.zip filter=lfs diff=lfs merge=lfs -text
26
  *.zstandard filter=lfs diff=lfs merge=lfs -text
27
  *tfevents* filter=lfs diff=lfs merge=lfs -text
 
 
25
  *.zip filter=lfs diff=lfs merge=lfs -text
26
  *.zstandard filter=lfs diff=lfs merge=lfs -text
27
  *tfevents* filter=lfs diff=lfs merge=lfs -text
28
+ *.mp4 filter=lfs diff=lfs merge=lfs -text
README.md ADDED
@@ -0,0 +1,28 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: stable-baselines3
3
+ tags:
4
+ - LunarLander-v2
5
+ - deep-reinforcement-learning
6
+ - reinforcement-learning
7
+ - stable-baselines3
8
+ model-index:
9
+ - name: PPO
10
+ results:
11
+ - metrics:
12
+ - type: mean_reward
13
+ value: 252.23 +/- 33.93
14
+ name: mean_reward
15
+ task:
16
+ type: reinforcement-learning
17
+ name: reinforcement-learning
18
+ dataset:
19
+ name: LunarLander-v2
20
+ type: LunarLander-v2
21
+ ---
22
+
23
+ # **PPO** Agent playing **LunarLander-v2**
24
+ This is a trained model of a **PPO** agent playing **LunarLander-v2** using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
25
+
26
+ ## Usage (with Stable-baselines3)
27
+ TODO: Add your code
28
+
config.json ADDED
@@ -0,0 +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 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 0x7f8eef982d40>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f8eef982dd0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f8eef982e60>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f8eef982ef0>", "_build": "<function ActorCriticPolicy._build at 0x7f8eef982f80>", "forward": "<function ActorCriticPolicy.forward at 0x7f8eef98b050>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f8eef98b0e0>", "_predict": "<function ActorCriticPolicy._predict at 0x7f8eef98b170>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f8eef98b200>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f8eef98b290>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f8eef98b320>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f8eef9d3990>"}, "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": 18, "num_timesteps": 516096, "_total_timesteps": 500000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1652214701.0568547, "learning_rate": 0.0003, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVtQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJZAAgAAAAAAAI1ojr32xF+6eqsbOtHbRbYdZ0+68IkvuQAAgD8AAIA/AG2lvBTIjbpy7Dk7D+UVOAI8IDqgUeq5AACAPwAAgD+aayE8XGMkuhq5FTxH91M0r6FHultziTMAAIA/AACAPwB67zxc20K6Jdx8uU2q6rNKBKa6/GWPOAAAgD8AAIA/QFjAPfYYbLoCT4S6Bn8vs2YwvrtSP3QzAACAPwAAgD/Nx129jw5BumJIHjxE0e41CmClun2c6DQAAIA/AACAP21VP77Rq2c/owk5vqx8vL7j0lS+Ym0QPQAAAAAAAAAAGp6CPSdolz727jm+e4eOvutpur2MYMa9AAAAAAAAAADNGq+9EjVmPqovkD6prJ2+I1o5Pm5mCD4AAAAAAAAAAJpkEz0pJE26+P3TOyqx3jdLL/a6s4GaNgAAgD8AAIA/ZmdpPT3aZLlRjEE5ZlWqM9dpUzliIGW4AACAPwAAgD9m1f28jwZeul5WOTukPg60uMCzu8IXi7MAAIA/AACAP2YHx7xBie09sG/wPKNumL73uTO8gzZ6vAAAAAAAAAAAc4vJvSnoQLprAz26pnbQtHL9jjqDXFo5AACAPwAAgD+zVtG9mwhSPxIdBD4pMPy+LcXDvfZxMj4AAAAAAAAAAJoRfLzDOSa6LHI5ubEmezbV+Eg7GpFYOAAAgD8AAIA/ms+TvPZQMbpDAFS5AGBNsGCoDLsq3Hc4AACAPwAAgD/NFJ+8s7rBPhbngr3VooK+CYIbPRAOrb0AAAAAAAAAAJSMBW51bXB5lIwFZHR5cGWUk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGJLEksIhpSMAUOUdJRSlC4="}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVhQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYSAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAJSMBW51bXB5lIwFZHR5cGWUk5SMAmIxlImIh5RSlChLA4wBfJROTk5K/////0r/////SwB0lGJLEoWUjAFDlHSUUpQu"}, "_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": 280, "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": 10, "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-cufa.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:d6504ec6e38fb83965af3782ce537f3382dd0cc62ca0e3140096f40b33e32f33
3
+ size 144181
ppo-LunarLander-v2-cufa/_stable_baselines3_version ADDED
@@ -0,0 +1 @@
 
 
1
+ 1.5.0
ppo-LunarLander-v2-cufa/data ADDED
@@ -0,0 +1,94 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "policy_class": {
3
+ ":type:": "<class 'abc.ABCMeta'>",
4
+ ":serialized:": "gAWVOwAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMEUFjdG9yQ3JpdGljUG9saWN5lJOULg==",
5
+ "__module__": "stable_baselines3.common.policies",
6
+ "__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 ",
7
+ "__init__": "<function ActorCriticPolicy.__init__ at 0x7f8eef982d40>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f8eef982dd0>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f8eef982e60>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f8eef982ef0>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7f8eef982f80>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7f8eef98b050>",
13
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f8eef98b0e0>",
14
+ "_predict": "<function ActorCriticPolicy._predict at 0x7f8eef98b170>",
15
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f8eef98b200>",
16
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f8eef98b290>",
17
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f8eef98b320>",
18
+ "__abstractmethods__": "frozenset()",
19
+ "_abc_impl": "<_abc_data object at 0x7f8eef9d3990>"
20
+ },
21
+ "verbose": 1,
22
+ "policy_kwargs": {},
23
+ "observation_space": {
24
+ ":type:": "<class 'gym.spaces.box.Box'>",
25
+ ":serialized:": "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",
26
+ "dtype": "float32",
27
+ "_shape": [
28
+ 8
29
+ ],
30
+ "low": "[-inf -inf -inf -inf -inf -inf -inf -inf]",
31
+ "high": "[inf inf inf inf inf inf inf inf]",
32
+ "bounded_below": "[False False False False False False False False]",
33
+ "bounded_above": "[False False False False False False False False]",
34
+ "_np_random": null
35
+ },
36
+ "action_space": {
37
+ ":type:": "<class 'gym.spaces.discrete.Discrete'>",
38
+ ":serialized:": "gAWVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu",
39
+ "n": 4,
40
+ "_shape": [],
41
+ "dtype": "int64",
42
+ "_np_random": null
43
+ },
44
+ "n_envs": 18,
45
+ "num_timesteps": 516096,
46
+ "_total_timesteps": 500000,
47
+ "_num_timesteps_at_start": 0,
48
+ "seed": null,
49
+ "action_noise": null,
50
+ "start_time": 1652214701.0568547,
51
+ "learning_rate": 0.0003,
52
+ "tensorboard_log": null,
53
+ "lr_schedule": {
54
+ ":type:": "<class 'function'>",
55
+ ":serialized:": "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"
56
+ },
57
+ "_last_obs": {
58
+ ":type:": "<class 'numpy.ndarray'>",
59
+ ":serialized:": "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"
60
+ },
61
+ "_last_episode_starts": {
62
+ ":type:": "<class 'numpy.ndarray'>",
63
+ ":serialized:": "gAWVhQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYSAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAJSMBW51bXB5lIwFZHR5cGWUk5SMAmIxlImIh5RSlChLA4wBfJROTk5K/////0r/////SwB0lGJLEoWUjAFDlHSUUpQu"
64
+ },
65
+ "_last_original_obs": null,
66
+ "_episode_num": 0,
67
+ "use_sde": false,
68
+ "sde_sample_freq": -1,
69
+ "_current_progress_remaining": -0.032192,
70
+ "ep_info_buffer": {
71
+ ":type:": "<class 'collections.deque'>",
72
+ ":serialized:": "gAWVfBAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMI2GK3zypeY0CUhpRSlIwBbJRN6AOMAXSUR0CJD0t3fQ8fdX2UKGgGaAloD0MIADs3bcYcZ0CUhpRSlGgVTegDaBZHQIkQt7pmmLt1fZQoaAZoCWgPQwgYXknyXOBjQJSGlFKUaBVN6ANoFkdAiRMeJgsshHV9lChoBmgJaA9DCAwCK4eWHmBAlIaUUpRoFU3oA2gWR0CJr3fhMrVfdX2UKGgGaAloD0MIPV+zXLblYUCUhpRSlGgVTegDaBZHQImzU7IT4+N1fZQoaAZoCWgPQwjekhywK5RjQJSGlFKUaBVN6ANoFkdAibdYJu2qk3V9lChoBmgJaA9DCAnFVtC0zGJAlIaUUpRoFU3oA2gWR0CJvQXDWK/EdX2UKGgGaAloD0MIPpP987R4aECUhpRSlGgVTegDaBZHQIm/Hfdhy811fZQoaAZoCWgPQwgH0zB8RDNgQJSGlFKUaBVN6ANoFkdAicE1YyO7x3V9lChoBmgJaA9DCF4wuOYO22JAlIaUUpRoFU3oA2gWR0CJxASkCV8kdX2UKGgGaAloD0MIiSXl7vPTYECUhpRSlGgVTegDaBZHQInG5NdqtYB1fZQoaAZoCWgPQwgCKEaWTP1jQJSGlFKUaBVN6ANoFkdAicfdG7SRbXV9lChoBmgJaA9DCJvIzAWugmRAlIaUUpRoFU3oA2gWR0CJ7hNXYDkmdX2UKGgGaAloD0MINzP60fBfYUCUhpRSlGgVTegDaBZHQIob6vkili11fZQoaAZoCWgPQwi9xi5RvbVgQJSGlFKUaBVN6ANoFkdAiiKbcwg1WXV9lChoBmgJaA9DCFX6CWe3s19AlIaUUpRoFU3oA2gWR0CKI9jslb/wdX2UKGgGaAloD0MI0lW6u07DYUCUhpRSlGgVTegDaBZHQIokF+TeO4p1fZQoaAZoCWgPQwhz1qccE5xkQJSGlFKUaBVN6ANoFkdAiigRri2lVXV9lChoBmgJaA9DCIhjXdxG5mJAlIaUUpRoFU3oA2gWR0CKNZsguAZsdX2UKGgGaAloD0MIQMBatethZECUhpRSlGgVTegDaBZHQIo3F7laKUF1fZQoaAZoCWgPQwh8m/7sR2tlQJSGlFKUaBVN6ANoFkdAijlm/vfCRHV9lChoBmgJaA9DCKD/Hrz2emVAlIaUUpRoFU3oA2gWR0CKOlSMLncMdX2UKGgGaAloD0MI5dNjWwakQkCUhpRSlGgVS7FoFkdAijwcRcu8LHV9lChoBmgJaA9DCIUmiSXl8WVAlIaUUpRoFU3oA2gWR0CK2Hf779AHdX2UKGgGaAloD0MIKCuGq4MCZUCUhpRSlGgVTegDaBZHQIrcavFFUhp1fZQoaAZoCWgPQwhXeJeL+JxRQJSGlFKUaBVN6ANoFkdAiuHLoGIKt3V9lChoBmgJaA9DCF6+9WE9gGNAlIaUUpRoFU3oA2gWR0CK47j4HoovdX2UKGgGaAloD0MIHJlH/uAdYkCUhpRSlGgVTegDaBZHQIrlnTiKiwl1fZQoaAZoCWgPQwjvObAcISlLQJSGlFKUaBVLw2gWR0CK5+3I+4b0dX2UKGgGaAloD0MIvASnPpDqY0CUhpRSlGgVTegDaBZHQIrn/3ai9Ix1fZQoaAZoCWgPQwj04O6s3UJfQJSGlFKUaBVN6ANoFkdAiuqpGFzuGHV9lChoBmgJaA9DCFh06zW9k2ZAlIaUUpRoFU3oA2gWR0CK64Oby6MBdX2UKGgGaAloD0MIZLDiVGutQECUhpRSlGgVS7poFkdAivV+l9BrvnV9lChoBmgJaA9DCKaaWUsBvTBAlIaUUpRoFUuyaBZHQIsNkwvg3tN1fZQoaAZoCWgPQwiF0hdCzjZjQJSGlFKUaBVN6ANoFkdAixAnOSntOXV9lChoBmgJaA9DCLH7juGxkGVAlIaUUpRoFU3oA2gWR0CLPzkDIRywdX2UKGgGaAloD0MImGw82OJ1ZkCUhpRSlGgVTegDaBZHQItGYCMglnh1fZQoaAZoCWgPQwhcWaKzzHpiQJSGlFKUaBVN6ANoFkdAi0fqIrOJL3V9lChoBmgJaA9DCGyvBb03fFtAlIaUUpRoFU3oA2gWR0CLTHkvK2a2dX2UKGgGaAloD0MIIGEYsGTWZUCUhpRSlGgVTegDaBZHQItbZpeu3c51fZQoaAZoCWgPQwh5zEBl/INOQJSGlFKUaBVLv2gWR0CLXa606YE4dX2UKGgGaAloD0MIMPMd/MSMY0CUhpRSlGgVTegDaBZHQItf5M10knl1fZQoaAZoCWgPQwhqNLkYAyZlQJSGlFKUaBVN6ANoFkdAi2Dx1gYxcnV9lChoBmgJaA9DCBBaD18mRWZAlIaUUpRoFU3oA2gWR0CLYtSiudPMdX2UKGgGaAloD0MIhUGZRhPOY0CUhpRSlGgVTegDaBZHQItlL9S/CZZ1fZQoaAZoCWgPQwgh6GhVS51kQJSGlFKUaBVN6ANoFkdAjAUF8PWhAXV9lChoBmgJaA9DCB5uh4bF1WdAlIaUUpRoFU3oA2gWR0CMDWBikO7QdX2UKGgGaAloD0MIAHUDBV5uYUCUhpRSlGgVTegDaBZHQIwPtQ40dil1fZQoaAZoCWgPQwhxPJ8BdetlQJSGlFKUaBVN6ANoFkdAjBJlXaJyhnV9lChoBmgJaA9DCAIOoUrNZ2FAlIaUUpRoFU3oA2gWR0CMEn0wrUb2dX2UKGgGaAloD0MIo8nFGFhAYUCUhpRSlGgVTegDaBZHQIwVNf3N9ph1fZQoaAZoCWgPQwg1s5YC0vViQJSGlFKUaBVN6ANoFkdAjBYs0P6KtXV9lChoBmgJaA9DCPeTMT6MLnJAlIaUUpRoFU25AWgWR0CMNeJ0GNaRdX2UKGgGaAloD0MIfGKdKl8BZECUhpRSlGgVTegDaBZHQIw5JnUUfxN1fZQoaAZoCWgPQwi6o//l2iVlQJSGlFKUaBVN6ANoFkdAjDtp79hqkHV9lChoBmgJaA9DCNP2r6w0ZWdAlIaUUpRoFU3oA2gWR0CMbydhAnlXdX2UKGgGaAloD0MIGH0FacY9Y0CUhpRSlGgVTegDaBZHQIxwtZLZi/h1fZQoaAZoCWgPQwj3j4XokMhjQJSGlFKUaBVN6ANoFkdAjHUeBYmsvXV9lChoBmgJaA9DCDuKc9TRxGVAlIaUUpRoFU3oA2gWR0CMg29g4OtodX2UKGgGaAloD0MIelBQitYEZ0CUhpRSlGgVTegDaBZHQIyFj4agmJF1fZQoaAZoCWgPQwgkm6vmuRVmQJSGlFKUaBVN6ANoFkdAjIdi83++/XV9lChoBmgJaA9DCKRUwhN69mNAlIaUUpRoFU3oA2gWR0CMiG+GoJiRdX2UKGgGaAloD0MIa9WuCenOYECUhpRSlGgVTegDaBZHQIyMXC0ngHh1fZQoaAZoCWgPQwi5UzpY/2pgQJSGlFKUaBVN6ANoFkdAjJCwRPGhmHV9lChoBmgJaA9DCOnSvyQV0WJAlIaUUpRoFU3oA2gWR0CNNewu/UONdX2UKGgGaAloD0MIvt2SHDAFZUCUhpRSlGgVTegDaBZHQI04J4KQaJh1fZQoaAZoCWgPQwhbQdMSq/ZhQJSGlFKUaBVN6ANoFkdAjTr/dZaFEnV9lChoBmgJaA9DCNOiPsmddGFAlIaUUpRoFU3oA2gWR0CNOxm4iHIqdX2UKGgGaAloD0MInn3lQXo2ZkCUhpRSlGgVTegDaBZHQI0+GUKRdQh1fZQoaAZoCWgPQwiYamYthYdjQJSGlFKUaBVN6ANoFkdAjT8njp9qlHV9lChoBmgJaA9DCA75ZwbxHWNAlIaUUpRoFU3oA2gWR0CNYUBshxHYdX2UKGgGaAloD0MIbamDvB5sYkCUhpRSlGgVTegDaBZHQI1kubPQfIV1fZQoaAZoCWgPQwiVRWEXxZlmQJSGlFKUaBVN6ANoFkdAjWcf7SApa3V9lChoBmgJaA9DCAAd5suLtmNAlIaUUpRoFU3oA2gWR0CNnTF/hESedX2UKGgGaAloD0MIx4Ds9W7nY0CUhpRSlGgVTegDaBZHQI2e1UIcBEN1fZQoaAZoCWgPQwhdwMsMmzRiQJSGlFKUaBVN6ANoFkdAjaN60Y0l7nV9lChoBmgJaA9DCNP1RNeFcWJAlIaUUpRoFU3oA2gWR0CNsfTNt65YdX2UKGgGaAloD0MIFO0qpPwEVUCUhpRSlGgVTegDaBZHQI20NLFn7Hh1fZQoaAZoCWgPQwivfQG9cGRkQJSGlFKUaBVN6ANoFkdAjbYkSuhbn3V9lChoBmgJaA9DCOuLhLac9GdAlIaUUpRoFU3oA2gWR0CNt0p2ll9SdX2UKGgGaAloD0MIndUCe0zDVkCUhpRSlGgVTegDaBZHQI27clHBk7R1fZQoaAZoCWgPQwj4pX7eVMtfQJSGlFKUaBVN6ANoFkdAjb/ZTAFgUnV9lChoBmgJaA9DCIviVdY2Y2FAlIaUUpRoFU3oA2gWR0COZQKziS7odX2UKGgGaAloD0MImL9C5sqcZkCUhpRSlGgVTegDaBZHQI5nPJRwZO11fZQoaAZoCWgPQwixGHWtvWFiQJSGlFKUaBVN6ANoFkdAjmoMyi22HHV9lChoBmgJaA9DCD4ipkSScGBAlIaUUpRoFU3oA2gWR0COaiV/tpmFdX2UKGgGaAloD0MIz2bV52qDY0CUhpRSlGgVTegDaBZHQI5tB7Vrhzh1fZQoaAZoCWgPQwjZe/FF+x5iQJSGlFKUaBVN6ANoFkdAjm4LORkmQnV9lChoBmgJaA9DCBdIUPyYlGBAlIaUUpRoFU3oA2gWR0COjlu+h4+sdX2UKGgGaAloD0MI7tEb7iMnX0CUhpRSlGgVTegDaBZHQI6RYx+KCQN1fZQoaAZoCWgPQwhpxMw+jwhlQJSGlFKUaBVN6ANoFkdAjpPCqZML4XV9lChoBmgJaA9DCI/k8h9SsGNAlIaUUpRoFU3oA2gWR0COw4GXXyy2dX2UKGgGaAloD0MIbD1DOOZbYECUhpRSlGgVTegDaBZHQI7E3cpLEk11fZQoaAZoCWgPQwjbGaa21N9mQJSGlFKUaBVN6ANoFkdAjsi6kIomX3V9lChoBmgJaA9DCBAlWvL4SWRAlIaUUpRoFU3oA2gWR0CO1gVh1DBudX2UKGgGaAloD0MInl4pyxAyYkCUhpRSlGgVTegDaBZHQI7YEQwsXi11fZQoaAZoCWgPQwhb6iCvh4BiQJSGlFKUaBVN6ANoFkdAjtneTNdJKHV9lChoBmgJaA9DCBXJVwKpimFAlIaUUpRoFU3oA2gWR0CO2sd3jdYXdX2UKGgGaAloD0MInOEGfP4bYUCUhpRSlGgVTegDaBZHQI7es+HJtBR1fZQoaAZoCWgPQwhC6nb2FXdgQJSGlFKUaBVN6ANoFkdAjuK/WlMyrXVlLg=="
73
+ },
74
+ "ep_success_buffer": {
75
+ ":type:": "<class 'collections.deque'>",
76
+ ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
77
+ },
78
+ "_n_updates": 280,
79
+ "n_steps": 1024,
80
+ "gamma": 0.999,
81
+ "gae_lambda": 0.98,
82
+ "ent_coef": 0.01,
83
+ "vf_coef": 0.5,
84
+ "max_grad_norm": 0.5,
85
+ "batch_size": 64,
86
+ "n_epochs": 10,
87
+ "clip_range": {
88
+ ":type:": "<class 'function'>",
89
+ ":serialized:": "gAWVvwIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwNX2J1aWx0aW5fdHlwZZSTlIwKTGFtYmRhVHlwZZSFlFKUKGgCjAhDb2RlVHlwZZSFlFKUKEsBSwBLAUsBSxNDBIgAUwCUToWUKYwBX5SFlIxIL3Vzci9sb2NhbC9saWIvcHl0aG9uMy43L2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lIwEZnVuY5RLgEMCAAGUjAN2YWyUhZQpdJRSlH2UKIwLX19wYWNrYWdlX1+UjBhzdGFibGVfYmFzZWxpbmVzMy5jb21tb26UjAhfX25hbWVfX5SMHnN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi51dGlsc5SMCF9fZmlsZV9flIxIL3Vzci9sb2NhbC9saWIvcHl0aG9uMy43L2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaCB9lH2UKGgXaA6MDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgYjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz/JmZmZmZmahZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"
90
+ },
91
+ "clip_range_vf": null,
92
+ "normalize_advantage": true,
93
+ "target_kl": null
94
+ }
ppo-LunarLander-v2-cufa/policy.optimizer.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:9609e09ed5902a822195dee0b58de86f250b2e1934d5ef107310314397c0b7ec
3
+ size 84893
ppo-LunarLander-v2-cufa/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:6f75bc90dcb1842b0d3f34000bb93176a0be4428464b11fb76147b89bc7245a9
3
+ size 43201
ppo-LunarLander-v2-cufa/pytorch_variables.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:d030ad8db708280fcae77d87e973102039acd23a11bdecc3db8eb6c0ac940ee1
3
+ size 431
ppo-LunarLander-v2-cufa/system_info.txt ADDED
@@ -0,0 +1,7 @@
 
 
 
 
 
 
 
 
1
+ OS: Linux-5.4.188+-x86_64-with-Ubuntu-18.04-bionic #1 SMP Sun Apr 24 10:03:06 PDT 2022
2
+ Python: 3.7.13
3
+ Stable-Baselines3: 1.5.0
4
+ PyTorch: 1.11.0+cu113
5
+ GPU Enabled: True
6
+ Numpy: 1.21.6
7
+ Gym: 0.21.0
replay.mp4 ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:e151ce588de4d51ab8fa1718c6d922af5dc96cc2f039f41ea0fe554d82c2bbc9
3
+ size 248593
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 252.233364204621, "std_reward": 33.92711992939137, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-05-10T20:51:14.471968"}