moisesrobles04 commited on
Commit
1fd4c82
·
1 Parent(s): cca4cac

Second Test

Browse files
README.md CHANGED
@@ -16,7 +16,7 @@ model-index:
16
  type: LunarLander-v2
17
  metrics:
18
  - type: mean_reward
19
- value: 161.92 +/- 119.28
20
  name: mean_reward
21
  verified: false
22
  ---
 
16
  type: LunarLander-v2
17
  metrics:
18
  - type: mean_reward
19
+ value: -21.59 +/- 79.61
20
  name: mean_reward
21
  verified: false
22
  ---
config.json CHANGED
@@ -1 +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 0x7f38bc9d1b40>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f38bc9d1bd0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f38bc9d1c60>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f38bc9d1cf0>", "_build": "<function ActorCriticPolicy._build at 0x7f38bc9d1d80>", "forward": "<function ActorCriticPolicy.forward at 0x7f38bc9d1e10>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f38bc9d1ea0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f38bc9d1f30>", "_predict": "<function ActorCriticPolicy._predict at 0x7f38bc9d1fc0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f38bc9d2050>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f38bc9d20e0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f38bc9d2170>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f38bc9c3040>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1689097572419026505, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAAIA5sD183f4+jdxkPFk4hr7rgV09PddsPQAAAAAAAAAAg3OMPs8NPz+GJtU9H/eQvuW+4j1S+1u9AAAAAAAAAAAAN6k9eUYKP6pFkr3Eh72+Oprvu/QMujwAAAAAAAAAAKVWpr5Xqgg8MLlcvH5Q3rkK7zW9VZKJOwAAgD8AAIA/TW73PcE5oj9WpZI+pED+vp2esz0b8108AAAAAAAAAADtMwS+9jiqPyjRJL821dy+Wm7yvWe3yr0AAAAAAAAAAEBSmD3K8gg+7sVjvb3V2r0m5Mk8ZlItvQAAAAAAAAAAhlMUPrNvJz8eUvs9UpybvqdDjT1j2i89AAAAAAAAAACzsBu++xGUO46b4rlfuk83ADUtvQ4BCDkAAIA/AACAP4Bng72hwgs/iHS0O3qQbr6S7mI8U1TePAAAAAAAAAAAswRCvmFhrLyboti7rudauoY7Gj7V5Sc7AACAPwAAgD9mAqO8MhCnP6OjVL4apwm/cgCYvNYtR70AAAAAAAAAAPYcWb7mcz4/265PvtDNt76KupG9Ej3xuwAAAAAAAAAATcakvjYzDj0uK1O89tanOZB1ML7FvJ87AACAPwAAgD8zQ5g63/3xPjfomL2nzZC+KjpJvE3xM7wAAAAAAAAAABr0TD5fAdU83ov4vYVVNDvdW6s+tIIVvgAAgD8AAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksQSwiGlIwBQ5R0lFKULg=="}, "_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": 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:": "gAWV1QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCloCmgOjApfbnBfcmFuZG9tlE51Yi4=", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "n_steps": 1024, "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": 5, "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": "3.10.12", "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"}}
 
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 0x7ec8f233b5b0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7ec8f233b640>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7ec8f233b6d0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7ec8f233b760>", "_build": "<function ActorCriticPolicy._build at 0x7ec8f233b7f0>", "forward": "<function ActorCriticPolicy.forward at 0x7ec8f233b880>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7ec8f233b910>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7ec8f233b9a0>", "_predict": "<function ActorCriticPolicy._predict at 0x7ec8f233ba30>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7ec8f233bac0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7ec8f233bb50>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7ec8f233bbe0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7ec8f233cd00>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1689616624059712644, "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": 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:": "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": 1228, "n_epochs": 5, "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-5.15.109+-x86_64-with-glibc2.31 # 1 SMP Fri Jun 9 10:57:30 UTC 2023", "Python": "3.10.12", "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.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:1170db8851b259890b5cdffa084455caddb67fb82ab7881d1969e114063e4d20
3
+ size 146760
ppo-LunarLander/_stable_baselines3_version ADDED
@@ -0,0 +1 @@
 
 
1
+ 2.0.0a5
ppo-LunarLander/data ADDED
@@ -0,0 +1,99 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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 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 ",
7
+ "__init__": "<function ActorCriticPolicy.__init__ at 0x7ec8f233b5b0>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7ec8f233b640>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7ec8f233b6d0>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7ec8f233b760>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7ec8f233b7f0>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7ec8f233b880>",
13
+ "extract_features": "<function ActorCriticPolicy.extract_features at 0x7ec8f233b910>",
14
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7ec8f233b9a0>",
15
+ "_predict": "<function ActorCriticPolicy._predict at 0x7ec8f233ba30>",
16
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7ec8f233bac0>",
17
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7ec8f233bb50>",
18
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7ec8f233bbe0>",
19
+ "__abstractmethods__": "frozenset()",
20
+ "_abc_impl": "<_abc._abc_data object at 0x7ec8f233cd00>"
21
+ },
22
+ "verbose": 1,
23
+ "policy_kwargs": {},
24
+ "num_timesteps": 1015808,
25
+ "_total_timesteps": 1000000,
26
+ "_num_timesteps_at_start": 0,
27
+ "seed": null,
28
+ "action_noise": null,
29
+ "start_time": 1689616624059712644,
30
+ "learning_rate": 0.0003,
31
+ "tensorboard_log": null,
32
+ "_last_obs": {
33
+ ":type:": "<class 'numpy.ndarray'>",
34
+ ":serialized:": "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"
35
+ },
36
+ "_last_episode_starts": {
37
+ ":type:": "<class 'numpy.ndarray'>",
38
+ ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="
39
+ },
40
+ "_last_original_obs": null,
41
+ "_episode_num": 0,
42
+ "use_sde": false,
43
+ "sde_sample_freq": -1,
44
+ "_current_progress_remaining": -0.015808000000000044,
45
+ "_stats_window_size": 100,
46
+ "ep_info_buffer": {
47
+ ":type:": "<class 'collections.deque'>",
48
+ ":serialized:": "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"
49
+ },
50
+ "ep_success_buffer": {
51
+ ":type:": "<class 'collections.deque'>",
52
+ ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
53
+ },
54
+ "_n_updates": 310,
55
+ "observation_space": {
56
+ ":type:": "<class 'gymnasium.spaces.box.Box'>",
57
+ ":serialized:": "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",
58
+ "dtype": "float32",
59
+ "bounded_below": "[ True True True True True True True True]",
60
+ "bounded_above": "[ True True True True True True True True]",
61
+ "_shape": [
62
+ 8
63
+ ],
64
+ "low": "[-90. -90. -5. -5. -3.1415927 -5.\n -0. -0. ]",
65
+ "high": "[90. 90. 5. 5. 3.1415927 5.\n 1. 1. ]",
66
+ "low_repr": "[-90. -90. -5. -5. -3.1415927 -5.\n -0. -0. ]",
67
+ "high_repr": "[90. 90. 5. 5. 3.1415927 5.\n 1. 1. ]",
68
+ "_np_random": null
69
+ },
70
+ "action_space": {
71
+ ":type:": "<class 'gymnasium.spaces.discrete.Discrete'>",
72
+ ":serialized:": "gAWV1QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCloCmgOjApfbnBfcmFuZG9tlE51Yi4=",
73
+ "n": "4",
74
+ "start": "0",
75
+ "_shape": [],
76
+ "dtype": "int64",
77
+ "_np_random": null
78
+ },
79
+ "n_envs": 16,
80
+ "n_steps": 1024,
81
+ "gamma": 0.999,
82
+ "gae_lambda": 0.98,
83
+ "ent_coef": 0.01,
84
+ "vf_coef": 0.5,
85
+ "max_grad_norm": 0.5,
86
+ "batch_size": 1228,
87
+ "n_epochs": 5,
88
+ "clip_range": {
89
+ ":type:": "<class 'function'>",
90
+ ":serialized:": "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"
91
+ },
92
+ "clip_range_vf": null,
93
+ "normalize_advantage": true,
94
+ "target_kl": null,
95
+ "lr_schedule": {
96
+ ":type:": "<class 'function'>",
97
+ ":serialized:": "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"
98
+ }
99
+ }
ppo-LunarLander/policy.optimizer.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:5e0d15b4f7b2233851bd188c7b9c6933f2a37ba63dd2790962afd645caace54a
3
+ size 87929
ppo-LunarLander/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:627a37b1ae9f61b6a2e5d724d51c577eecda45fd115930b5c17e5852fd7ee5f5
3
+ size 43329
ppo-LunarLander/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/system_info.txt ADDED
@@ -0,0 +1,9 @@
 
 
 
 
 
 
 
 
 
 
1
+ - OS: Linux-5.15.109+-x86_64-with-glibc2.31 # 1 SMP Fri Jun 9 10:57:30 UTC 2023
2
+ - Python: 3.10.12
3
+ - Stable-Baselines3: 2.0.0a5
4
+ - PyTorch: 2.0.1+cu118
5
+ - GPU Enabled: True
6
+ - Numpy: 1.22.4
7
+ - Cloudpickle: 2.2.1
8
+ - Gymnasium: 0.28.1
9
+ - OpenAI Gym: 0.25.2
replay.mp4 CHANGED
Binary files a/replay.mp4 and b/replay.mp4 differ
 
results.json CHANGED
@@ -1 +1 @@
1
- {"mean_reward": 161.92269889999997, "std_reward": 119.2801701090272, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-07-11T18:20:19.366026"}
 
1
+ {"mean_reward": -21.5903928, "std_reward": 79.60958251325924, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-07-17T18:17:38.102936"}