ethompson93 commited on
Commit
127ddbc
1 Parent(s): 556a300

uploading trained model

Browse files
README.md CHANGED
@@ -16,7 +16,7 @@ model-index:
16
  type: LunarLander-v2
17
  metrics:
18
  - type: mean_reward
19
- value: 241.80 +/- 47.99
20
  name: mean_reward
21
  verified: false
22
  ---
 
16
  type: LunarLander-v2
17
  metrics:
18
  - type: mean_reward
19
+ value: 280.56 +/- 17.70
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 0x7d68212dbd00>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7d68212dbd90>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7d68212dbe20>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7d68212dbeb0>", "_build": "<function ActorCriticPolicy._build at 0x7d68212dbf40>", "forward": "<function ActorCriticPolicy.forward at 0x7d68212e0040>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7d68212e00d0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7d68212e0160>", "_predict": "<function ActorCriticPolicy._predict at 0x7d68212e01f0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7d68212e0280>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7d68212e0310>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7d68212e03a0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7d6821276c40>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1701265943314364049, "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": 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-5.15.120+-x86_64-with-glibc2.35 # 1 SMP Wed Aug 30 11:19:59 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.1.0+cu118", "GPU Enabled": "True", "Numpy": "1.23.5", "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 0x79c4c412d3f0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x79c4c412d480>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x79c4c412d510>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x79c4c412d5a0>", "_build": "<function ActorCriticPolicy._build at 0x79c4c412d630>", "forward": "<function ActorCriticPolicy.forward at 0x79c4c412d6c0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x79c4c412d750>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x79c4c412d7e0>", "_predict": "<function ActorCriticPolicy._predict at 0x79c4c412d870>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x79c4c412d900>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x79c4c412d990>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x79c4c412da20>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x79c4cdf782c0>"}, "verbose": true, "policy_kwargs": {}, "num_timesteps": 2031616, "_total_timesteps": 2000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1701271916978344444, "learning_rate": 0.0004, "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": 620, "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": 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-5.15.120+-x86_64-with-glibc2.35 # 1 SMP Wed Aug 30 11:19:59 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.1.0+cu118", "GPU Enabled": "True", "Numpy": "1.23.5", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}
ppo-LunarLander-v2.zip CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:3543cf1bd6c0ed871cc9b6c57243a8dd10a9302e3be6a1f37ccf9e298ba58b2f
3
- size 147957
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:37b9e717a514c9bacf22432af9e522800fa346d0d64085b18d65c0fceb01e333
3
+ size 147924
ppo-LunarLander-v2/data CHANGED
@@ -4,34 +4,34 @@
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 0x7d68212dbd00>",
8
- "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7d68212dbd90>",
9
- "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7d68212dbe20>",
10
- "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7d68212dbeb0>",
11
- "_build": "<function ActorCriticPolicy._build at 0x7d68212dbf40>",
12
- "forward": "<function ActorCriticPolicy.forward at 0x7d68212e0040>",
13
- "extract_features": "<function ActorCriticPolicy.extract_features at 0x7d68212e00d0>",
14
- "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7d68212e0160>",
15
- "_predict": "<function ActorCriticPolicy._predict at 0x7d68212e01f0>",
16
- "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7d68212e0280>",
17
- "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7d68212e0310>",
18
- "predict_values": "<function ActorCriticPolicy.predict_values at 0x7d68212e03a0>",
19
  "__abstractmethods__": "frozenset()",
20
- "_abc_impl": "<_abc._abc_data object at 0x7d6821276c40>"
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": 1701265943314364049,
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'>",
@@ -45,13 +45,13 @@
45
  "_stats_window_size": 100,
46
  "ep_info_buffer": {
47
  ":type:": "<class 'collections.deque'>",
48
- ":serialized:": "gAWV+QsAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpRHQHGjl6NVBD6MAWyUS+mMAXSUR0Cb7Q5GSZBtdX2UKGgGR0Bwj7jn3cpLaAdLvGgIR0Cb7UGfPHDKdX2UKGgGR0BvLPyLAHmjaAdLumgIR0Cb7uEDyOJddX2UKGgGR0Bxq4Bfa6BiaAdL9WgIR0Cb7vNaQmu1dX2UKGgGR0BNQsNlRP43aAdLp2gIR0Cb7yO3UhFFdX2UKGgGR0BxoyaiKziTaAdL4WgIR0Cb8FO0svqUdX2UKGgGR0Bw1DWkJrtWaAdLrWgIR0Cb8sUPQOWjdX2UKGgGR0BwQF+F10T2aAdLt2gIR0Cb8xkCV8kVdX2UKGgGR0BxMIKgIyCWaAdNDAFoCEdAm/MrBO58SnV9lChoBkdActGyI55qumgHTT4BaAhHQJvzXU3GXHB1fZQoaAZHQGOWj2Bas6toB03oA2gIR0Cb82ysjmjkdX2UKGgGR0BxCzzK9wm3aAdL/GgIR0Cb87GBWgezdX2UKGgGR0BwS1SZSeiBaAdLyWgIR0Cb9EnQpnYhdX2UKGgGR0BxZhWfbsWwaAdNegFoCEdAm/RHBHkLhXV9lChoBkdAcTSCemNzbWgHS61oCEdAm/SAuh9LH3V9lChoBkdAbx4knkT6BWgHS8RoCEdAm/TXcclw+HV9lChoBkdAcVkclgMMJGgHTRoBaAhHQJv2KQCCBf91fZQoaAZHQHEPUGeMAFRoB009AWgIR0Cb9qjFQ2uQdX2UKGgGR0BxtV/Tb349aAdL4mgIR0Cb9tswL3K0dX2UKGgGR0BuWR0bLlmwaAdLsWgIR0Cb98Y/mknDdX2UKGgGR0By265iExqPaAdNNAFoCEdAm/fVs54nnnV9lChoBkdAcqarBj4Ho2gHS59oCEdAm/hhQFcIJXV9lChoBkdAbmWaP0Zm7WgHS9ZoCEdAm/j1twaR6nV9lChoBkdAcCjx8lXzUmgHS+RoCEdAm/lLSE12q3V9lChoBkdAciOK2rn1WmgHS6toCEdAm/lX1anrIHV9lChoBkdAcuaglF+d9WgHS8hoCEdAm/m7qMWGh3V9lChoBkdAcntLYf4h2WgHTQUBaAhHQJv5ubZvkzZ1fZQoaAZHQHG4Hx4IKMNoB0vtaAhHQJv53AoG6f91fZQoaAZHQG9uYTCcf/5oB00EAWgIR0Cb+vd5Y5ktdX2UKGgGR0ByVs8SwnpjaAdLs2gIR0Cb+0XpW3jNdX2UKGgGR0Bf9KSTyJ9BaAdN6ANoCEdAm/trUoa1kXV9lChoBkdAbUdXWe6I32gHS9hoCEdAm/uwFLWZqnV9lChoBkdAcQK6AOJ+D2gHS8poCEdAm/vw7DEWI3V9lChoBkdAbrO/eLvTgGgHS6hoCEdAm/v3zg/C7HV9lChoBkdAb8BL+xW1dGgHS7JoCEdAm/2Cuhbno3V9lChoBkdAbdgo5PuXu2gHS8RoCEdAm/2xTKkl/3V9lChoBkdAcncldkauOmgHTRoBaAhHQJv+8BdUsFt1fZQoaAZHQHAFaziS7oVoB0vlaAhHQJv/GSntOVR1fZQoaAZHQDV6taIN3GJoB0uoaAhHQJv/Po3aSLZ1fZQoaAZHQHKg+1F6RhdoB00UAWgIR0Cb/4A08/2TdX2UKGgGR0BwuNs1sLv1aAdLp2gIR0Cb/6PWhAW0dX2UKGgGR0BwRKdPLxI8aAdL1GgIR0CcAYGm1pj+dX2UKGgGR0Bw0jWUbDMvaAdNHAFoCEdAnAHiO/+Kj3V9lChoBkdAcRQ5SWJJoWgHS8ZoCEdAnAIBO58Sf3V9lChoBkdAcfctKZlWfmgHTSkBaAhHQJwCMGmk30h1fZQoaAZHQHCGQI2OyVxoB0vvaAhHQJwDEBsANod1fZQoaAZHQHD+zXarWAhoB0v+aAhHQJwEDHbRF7V1fZQoaAZHQG9zXu/k/8loB0uSaAhHQJwEodyT6i11fZQoaAZHQGJg4pc5bQloB03oA2gIR0CcBdO9WZJDdX2UKGgGR0BwMeU3XI2gaAdL7GgIR0CcBfX2ugYhdX2UKGgGR0BwvtWHUMG5aAdLuGgIR0CcBgDvVmSRdX2UKGgGR0Bx496ol2NeaAdNlQFoCEdAnAY7XtjTa3V9lChoBkdAR2yqfe1rqWgHS3toCEdAnAZy4J/oaHV9lChoBkdAb6Z9tMwlB2gHS9VoCEdAnAbRT4tYjnV9lChoBkdAca0BLwnYx2gHS8hoCEdAnAbjfFaStHV9lChoBkdAcfIbypaRp2gHS69oCEdAnAfIcebNKXV9lChoBkdAcQedS2phnmgHTRoBaAhHQJwJpaaCtih1fZQoaAZHQE/CLl3hXKdoB0t6aAhHQJwJ7YL9deJ1fZQoaAZHQG+RgMc6vJRoB0vhaAhHQJwKALkS26V1fZQoaAZHQG7H+J53TuxoB0vNaAhHQJwLNzCDVYp1fZQoaAZHQHNGC/fwZwZoB00AAWgIR0CcDBOlO45MdX2UKGgGR0BwpbphWo3raAdLtWgIR0CcDG2MbWEsdX2UKGgGR0BxhFgx8D0UaAdL72gIR0CcDP2nbZezdX2UKGgGR0BxdmD/VAiWaAdL0mgIR0CcDQgH/tIDdX2UKGgGR0BuHw+UyHmBaAdLv2gIR0CcDUjGDL8rdX2UKGgGR0Bx9ySzPa+OaAdL42gIR0CcDZJkoWpIdX2UKGgGR0BxzGATZg5SaAdL62gIR0CcD4i97F85dX2UKGgGR0ByTUh0Qsf8aAdNnwFoCEdAnBAIFNcnmnV9lChoBkdAQlD6eoUBXGgHS8doCEdAnBAoTfzjFXV9lChoBkdAcrEK4x1xKmgHTSkBaAhHQJwQfyUcGTt1fZQoaAZHQGRrMqz7di5oB03oA2gIR0CcESnM+u/2dX2UKGgGR0ByZ+LCN0eVaAdL6GgIR0CcEUWIGhVVdX2UKGgGR0BKHqMefZmJaAdLw2gIR0CcEcmmLtNSdX2UKGgGR0BwrVIlMRHxaAdLwWgIR0CcEnbEgntwdX2UKGgGR0Bxb4yXUpd9aAdL12gIR0CcEpcclw98dX2UKGgGR0Bx/ltIkJKKaAdLvGgIR0CcEqPw/gR9dX2UKGgGR0Bwrq+De0ojaAdL5WgIR0CcE3bt7a7FdX2UKGgGR0By5XeMyad+aAdL9GgIR0CcFG/xlQMydX2UKGgGR0BxKTKxLTQWaAdLtWgIR0CcFO/p+tr9dX2UKGgGR0ByasEwFkhBaAdL5mgIR0CcFeG7z06HdX2UKGgGR0BxwZt4zJp4aAdL92gIR0CcFwaiKziTdX2UKGgGR0BAfPA44p+daAdLfWgIR0CcFw3kxREXdX2UKGgGR0BxXmVdHDrJaAdL0WgIR0CcFx1Oj7AMdX2UKGgGR0BxDY1LrX18aAdL+GgIR0CcF2jCpFTedX2UKGgGR0BwgvSPU8V6aAdLvWgIR0CcF/sijcmCdX2UKGgGR0BwcaZssQNDaAdLyWgIR0CcGERJEpiJdX2UKGgGR0BxHTYODrZ8aAdL1WgIR0CcGH7HQyAQdX2UKGgGR0BPXglF+d9VaAdLhmgIR0CcGNlfJFLGdX2UKGgGR0ByOFOpKjBVaAdNFAFoCEdAnBmXz6JqI3V9lChoBkdAcMXJ79hqkGgHTWIBaAhHQJwbN/mT1TR1fZQoaAZHQHDSNuk1uR9oB0vyaAhHQJwbgasIVud1fZQoaAZHQHBZC1eBxxVoB0uoaAhHQJwb8R02cax1fZQoaAZHQHCjVmnO0LNoB0uvaAhHQJwcH+NtIkJ1fZQoaAZHQHEPLZFocrBoB0upaAhHQJwcUkcCHRF1fZQoaAZHQG7lrU9ZA6doB0u+aAhHQJwcpOoHcDd1fZQoaAZHQGDnhiLEUCdoB03oA2gIR0CcHSFGXokidX2UKGgGR0BwTX79AHE/aAdNDQFoCEdAnB25rLyMDXV9lChoBkdAb9uYJmdy1mgHS8toCEdAnB6raAWi13V9lChoBkdAcgHH80k4WGgHS+1oCEdAnB7JAQg9vHV9lChoBkdAcfvIKc/dI2gHS9BoCEdAnB+F3Qla83VlLg=="
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:": "gAWVcAIAAAAAAACMFGd5bW5hc2l1bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lGgFk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMDWJvdW5kZWRfYmVsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWCAAAAAAAAAABAQEBAQEBAZRoB4wCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksIhZSMAUOUdJRSlIwNYm91bmRlZF9hYm92ZZRoECiWCAAAAAAAAAABAQEBAQEBAZRoFEsIhZRoGHSUUpSMBl9zaGFwZZRLCIWUjANsb3eUaBAoliAAAAAAAAAAAAC0wgAAtMIAAKDAAACgwNsPScAAAKDAAAAAgAAAAICUaApLCIWUaBh0lFKUjARoaWdolGgQKJYgAAAAAAAAAAAAtEIAALRCAACgQAAAoEDbD0lAAACgQAAAgD8AAIA/lGgKSwiFlGgYdJRSlIwIbG93X3JlcHKUjFtbLTkwLiAgICAgICAgLTkwLiAgICAgICAgIC01LiAgICAgICAgIC01LiAgICAgICAgIC0zLjE0MTU5MjcgIC01LgogIC0wLiAgICAgICAgIC0wLiAgICAgICBdlIwJaGlnaF9yZXBylIxTWzkwLiAgICAgICAgOTAuICAgICAgICAgNS4gICAgICAgICA1LiAgICAgICAgIDMuMTQxNTkyNyAgNS4KICAxLiAgICAgICAgIDEuICAgICAgIF2UjApfbnBfcmFuZG9tlE51Yi4=",
@@ -94,6 +94,6 @@
94
  "target_kl": null,
95
  "lr_schedule": {
96
  ":type:": "<class 'function'>",
97
- ":serialized:": "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"
98
  }
99
  }
 
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 0x79c4c412d3f0>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x79c4c412d480>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x79c4c412d510>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x79c4c412d5a0>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x79c4c412d630>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x79c4c412d6c0>",
13
+ "extract_features": "<function ActorCriticPolicy.extract_features at 0x79c4c412d750>",
14
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x79c4c412d7e0>",
15
+ "_predict": "<function ActorCriticPolicy._predict at 0x79c4c412d870>",
16
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x79c4c412d900>",
17
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x79c4c412d990>",
18
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x79c4c412da20>",
19
  "__abstractmethods__": "frozenset()",
20
+ "_abc_impl": "<_abc._abc_data object at 0x79c4cdf782c0>"
21
  },
22
+ "verbose": true,
23
  "policy_kwargs": {},
24
+ "num_timesteps": 2031616,
25
+ "_total_timesteps": 2000000,
26
  "_num_timesteps_at_start": 0,
27
  "seed": null,
28
  "action_noise": null,
29
+ "start_time": 1701271916978344444,
30
+ "learning_rate": 0.0004,
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'>",
 
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": 620,
55
  "observation_space": {
56
  ":type:": "<class 'gymnasium.spaces.box.Box'>",
57
  ":serialized:": "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",
 
94
  "target_kl": null,
95
  "lr_schedule": {
96
  ":type:": "<class 'function'>",
97
+ ":serialized:": "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"
98
  }
99
  }
ppo-LunarLander-v2/policy.optimizer.pth CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:ef7eafe00c1c3ab5bcf5c2ee5b07896db021ec807eca16104308e5e346b0d95d
3
  size 88362
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:a42a8542a24b4cbfb376f11699f6bcb7bbb2d97689a38760b101596e54cf2f4e
3
  size 88362
ppo-LunarLander-v2/policy.pth CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:a6489a169a8da38c60de7b068976d3bed67cfb99767e02c1ecf865cf61fb8efa
3
  size 43762
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:6d6428082d2c5a24696ecaca1bddf76b55fc1e208e5c161622b867c4e691c04b
3
  size 43762
replay.mp4 CHANGED
Binary files a/replay.mp4 and b/replay.mp4 differ
 
results.json CHANGED
@@ -1 +1 @@
1
- {"mean_reward": 241.8030338, "std_reward": 47.98765827536724, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-11-29T14:20:12.520702"}
 
1
+ {"mean_reward": 280.5623284, "std_reward": 17.701553051937676, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-11-29T16:13:37.593927"}