PPO LunarLander-v2 trained agent 2
Browse files- README.md +37 -0
- config.json +1 -0
- ppo-LunarLander-v2-2.zip +3 -0
- ppo-LunarLander-v2-2/_stable_baselines3_version +1 -0
- ppo-LunarLander-v2-2/data +99 -0
- ppo-LunarLander-v2-2/policy.optimizer.pth +3 -0
- ppo-LunarLander-v2-2/policy.pth +3 -0
- ppo-LunarLander-v2-2/pytorch_variables.pth +3 -0
- ppo-LunarLander-v2-2/system_info.txt +9 -0
- replay.mp4 +0 -0
- results.json +1 -0
README.md
ADDED
@@ -0,0 +1,37 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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 |
+
- task:
|
12 |
+
type: reinforcement-learning
|
13 |
+
name: reinforcement-learning
|
14 |
+
dataset:
|
15 |
+
name: LunarLander-v2
|
16 |
+
type: LunarLander-v2
|
17 |
+
metrics:
|
18 |
+
- type: mean_reward
|
19 |
+
value: 258.18 +/- 14.50
|
20 |
+
name: mean_reward
|
21 |
+
verified: false
|
22 |
+
---
|
23 |
+
|
24 |
+
# **PPO** Agent playing **LunarLander-v2**
|
25 |
+
This is a trained model of a **PPO** agent playing **LunarLander-v2**
|
26 |
+
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
|
27 |
+
|
28 |
+
## Usage (with Stable-baselines3)
|
29 |
+
TODO: Add your code
|
30 |
+
|
31 |
+
|
32 |
+
```python
|
33 |
+
from stable_baselines3 import ...
|
34 |
+
from huggingface_sb3 import load_from_hub
|
35 |
+
|
36 |
+
...
|
37 |
+
```
|
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 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 0x7bb836e8ecb0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7bb836e8ed40>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7bb836e8edd0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7bb836e8ee60>", "_build": "<function ActorCriticPolicy._build at 0x7bb836e8eef0>", "forward": "<function ActorCriticPolicy.forward at 0x7bb836e8ef80>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7bb836e8f010>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7bb836e8f0a0>", "_predict": "<function ActorCriticPolicy._predict at 0x7bb836e8f130>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7bb836e8f1c0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7bb836e8f250>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7bb836e8f2e0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7bb836e31c00>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1736740216034055186, "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": 248, "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:": "gAWV2wAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgOjApfbnBfcmFuZG9tlE51Yi4=", "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": 64, "n_epochs": 4, "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-6.1.85+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Thu Jun 27 21:05:47 UTC 2024", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.5.1+cu121", "GPU Enabled": "False", "Numpy": "1.26.4", "Cloudpickle": "3.1.0", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}
|
ppo-LunarLander-v2-2.zip
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:04dfb26294bfb1cfdb83ce31e18b63ae8c5166eab25787aa322f4b92c914f028
|
3 |
+
size 147505
|
ppo-LunarLander-v2-2/_stable_baselines3_version
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
2.0.0a5
|
ppo-LunarLander-v2-2/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 0x7bb836e8ecb0>",
|
8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7bb836e8ed40>",
|
9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7bb836e8edd0>",
|
10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7bb836e8ee60>",
|
11 |
+
"_build": "<function ActorCriticPolicy._build at 0x7bb836e8eef0>",
|
12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x7bb836e8ef80>",
|
13 |
+
"extract_features": "<function ActorCriticPolicy.extract_features at 0x7bb836e8f010>",
|
14 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7bb836e8f0a0>",
|
15 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x7bb836e8f130>",
|
16 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7bb836e8f1c0>",
|
17 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7bb836e8f250>",
|
18 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7bb836e8f2e0>",
|
19 |
+
"__abstractmethods__": "frozenset()",
|
20 |
+
"_abc_impl": "<_abc._abc_data object at 0x7bb836e31c00>"
|
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": 1736740216034055186,
|
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:": "gAWVPwwAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpRHQHHDqpHZsbiMAWyUTS8BjAF0lEdAnpGN3Sro4nV9lChoBkdAbLf863iJf2gHTSYBaAhHQJ6S72L5ylx1fZQoaAZHQHC+VCojv/loB00kAWgIR0Cekvse4kNXdX2UKGgGR0BxkGfapPykaAdNNAFoCEdAnpSJ1/2Cd3V9lChoBkdAbUzuiN83M2gHTREBaAhHQJ6W++BYmsx1fZQoaAZHQHAYezIFNcpoB00xAWgIR0CemFAmReTndX2UKGgGR0BujFuYQarFaAdNUQFoCEdAnpilHFxXGXV9lChoBkdAbwiXsw+MZWgHTQ4BaAhHQJ6ZlO58Sf11fZQoaAZHQHDAc14xDb9oB00zAWgIR0CemamoBJZodX2UKGgGR0BxnwGFBY3eaAdNFQFoCEdAnpoCX6ZYxXV9lChoBkdAcbdbQkX1rmgHTRIBaAhHQJ6aRp0wJw91fZQoaAZHQG5uN/vv0AdoB00NAWgIR0Cemr29+PRzdX2UKGgGR0Bw7YRK6FufaAdNOQFoCEdAnps3l0YCQ3V9lChoBkdAb0FrKNhmXmgHTQwBaAhHQJ6bbCuU2UB1fZQoaAZHQHHiX/95yENoB03BAWgIR0Cem8K3NLUTdX2UKGgGR0ByIpEDyOJdaAdNDQFoCEdAnpvdZNfw7XV9lChoBkdAcf06vaDf32gHTRsBaAhHQJ6czHcUM5R1fZQoaAZHQHAhl72L5yloB001AWgIR0CenyMQmNR4dX2UKGgGR0Bw55+9alk6aAdNUQFoCEdAnqBRs2vSt3V9lChoBkdAbxJTH80k4WgHTTcBaAhHQJ6g+8oQWep1fZQoaAZHQG6ledkJ8fFoB00LAWgIR0CeoZD28IzFdX2UKGgGR0BwCGQaJhvzaAdNIQFoCEdAnqOhbB42THV9lChoBkdAbuv0knkT6GgHTRkBaAhHQJ6kiRaHKwJ1fZQoaAZHQG7CZKFqSHNoB00vAWgIR0CepJK2KEWZdX2UKGgGR0Bwkbq4YrJ9aAdNKwFoCEdAnqVcPatcOnV9lChoBkdAbfHXe3x4IWgHTRQBaAhHQJ6ljnNgSe11fZQoaAZHQHLMxreqJdloB004AWgIR0CepjOQyRCAdX2UKGgGR0ByERVea8YiaAdNHQFoCEdAnqamsmv4d3V9lChoBkdAb+pcEeQuEmgHTSEBaAhHQJ6nZT1kDp11fZQoaAZHQG7pzkZJkG1oB005AWgIR0Cep4LqUu+RdX2UKGgGR0BycHJPqLTAaAdNLQFoCEdAnqeyHymQ83V9lChoBkdAcDjCCz1K5GgHTWoBaAhHQJ6oTdO6/Zd1fZQoaAZHQHIOU4WDYiBoB01LAWgIR0Ceqb0iQkondX2UKGgGR0BvozZvkzXSaAdNHgFoCEdAnqpMLronr3V9lChoBkdARUS1TisGPmgHS+VoCEdAnqpWs3hn8XV9lChoBkdAcMPnLaEi+2gHTSYBaAhHQJ6rgsUZeiV1fZQoaAZHQHGoYNiH6/JoB00hAWgIR0Ceq+XhOxjbdX2UKGgGR0BwPEwh4dIYaAdNIQFoCEdAnq5aABkqc3V9lChoBkdATMS2WpqASWgHS+FoCEdAnq+Ph/Aj6nV9lChoBkdAcKEhBZ6lcmgHTTUBaAhHQJ6wDmq5sj51fZQoaAZHQG/ZHNX5nDloB00dAWgIR0CesBdfb9IgdX2UKGgGR0BxkzKFIuoQaAdNKgFoCEdAnrBprHlwLnV9lChoBkdAcbxmce8wpWgHTUABaAhHQJ6whbnoxHp1fZQoaAZHQHFDXw5NoJ1oB00VAWgIR0CeyhCHARChdX2UKGgGR0BykOGWUr08aAdNCQFoCEdAnspxisny/nV9lChoBkdAb6H+o99tuWgHTQQBaAhHQJ7KeOdXko51fZQoaAZHQHJO5jMFEApoB00yAWgIR0Ceyrnzg/C7dX2UKGgGR0BuuwUDdP+GaAdNHAFoCEdAnsv1psXSB3V9lChoBkdAcP9EZR8+imgHTQUBaAhHQJ7MqYLLIPt1fZQoaAZHQHLwRPKuB+ZoB00mAWgIR0Cezrtbs4T9dX2UKGgGR0BxMEPSUkfLaAdNMAFoCEdAns8by6MBIXV9lChoBkdAcUZ2bobGWGgHTRcBaAhHQJ7Pfw1BMSN1fZQoaAZHQHEwNtl7MPloB00qAWgIR0Ce0K7eVLSNdX2UKGgGR0Bsh+J1q33IaAdNDgFoCEdAntI2WUr08XV9lChoBkdAbjX7uUliSmgHTQsBaAhHQJ7TOfNA1Nx1fZQoaAZHQHEBnI2fkFRoB00NAWgIR0Ce1EjRD1GtdX2UKGgGR0BtPHktEofCaAdNFQFoCEdAntSCZ8a4t3V9lChoBkdAcg/eJYT0x2gHTSgBaAhHQJ7U96AvtdB1fZQoaAZHQHEv3J5mh/RoB00zAWgIR0Ce1WLpA2Q5dX2UKGgGR0BxonL1VYITaAdNHwFoCEdAntXLOu7pV3V9lChoBkdAcMZsVclgMWgHTTUBaAhHQJ7WPBpHqeN1fZQoaAZHQG7nAYP5HmRoB00+AWgIR0Ce1vEnb7CSdX2UKGgGR0Bxv+T6i0v5aAdNSgFoCEdAntek7CBPK3V9lChoBkdActI6gM+eOGgHTTQBaAhHQJ7Y7ELpiZx1fZQoaAZHQG9j5sbedkJoB00XAWgIR0Ce2k8XvYvndX2UKGgGR0BwINOmBOHnaAdNGAFoCEdAntrdL127nXV9lChoBkdAcikS2Yv38GgHS/xoCEdAntr2tuDSPXV9lChoBkdAcqz2f029+WgHTXQBaAhHQJ7bBv863iJ1fZQoaAZHQHBmNGEwnIBoB00yAWgIR0Ce2yp2U0N0dX2UKGgGR0Bwwtgtvn8saAdNCAFoCEdAnt3686FM7HV9lChoBkdAchu/lhgE2mgHTTkBaAhHQJ7e7T/hl191fZQoaAZHQG5541pCa7VoB00KAWgIR0Ce37v8IiTudX2UKGgGR0Byx2C5EtulaAdNLQFoCEdAnuCJU1hsqXV9lChoBkdAcecahpQDWGgHTS8BaAhHQJ7h3HdXT3J1fZQoaAZHQHDTm8RL9MtoB00mAWgIR0Ce4ox8UmD2dX2UKGgGR0BxElXjlxOtaAdNFwFoCEdAnuLENnXd03V9lChoBkdAcMLDwpe/pWgHTUMBaAhHQJ7jVutOmBR1fZQoaAZHQHC8+5jH4oJoB00WAWgIR0Ce45a/ATIvdX2UKGgGR0Bs8KIrOJLvaAdNcgFoCEdAnuP5JPIn0HV9lChoBkdAcjhntfG+9WgHTQIBaAhHQJ7kGzUqhDh1fZQoaAZHQFMktA9mpVFoB0v4aAhHQJ7laD+R5kd1fZQoaAZHQG1WwkxASnNoB00cAWgIR0Ce5q4j8k2QdX2UKGgGR0Bwbp52Qnx8aAdNMAFoCEdAnub/hhpg1HV9lChoBkdAb4fnLaEi+2gHTR8BaAhHQJ7nCqABkqd1fZQoaAZHQHA2AJswco9oB00lAWgIR0Ce5x9DQZ4wdX2UKGgGR0BxaXxOLzf8aAdNLAFoCEdAnunfBN21UnV9lChoBkdAcFqHGjsUqWgHTRQBaAhHQJ7p3bXYlIF1fZQoaAZHQHFjQcT8HfNoB00UAWgIR0Ce6pV6eGwidX2UKGgGR0BwVqajN6gNaAdNMQFoCEdAnuzRXGOuJXV9lChoBkdAbwQ/FirksGgHTRwBaAhHQJ7uX1Hvtt11fZQoaAZHQHHPfRE4NqhoB00SAWgIR0Ce7oBDXvphdX2UKGgGR0ByVSLQ5WBCaAdNKAFoCEdAnu7IYR/ViHV9lChoBkdAcq6v5gw482gHS+hoCEdAnu8JSJj2BnV9lChoBkdAb97g1m8M/mgHTTwBaAhHQJ7vGgDifg91fZQoaAZHQG5c2DYh+v1oB00VAWgIR0Ce72o9s7+2dX2UKGgGR0Bxg9VzZHuraAdNIQFoCEdAnu+MYZVGTnV9lChoBkdAbJ48jiXIEWgHTRgBaAhHQJ7vtgJC0F91fZQoaAZHQHI9wKfFrEdoB00aAWgIR0Ce8sqgyuZDdX2UKGgGR0BwZZ/Tb349aAdNFwFoCEdAnvNEb961LXV9lChoBkdAbrO7V8Ti82gHTR8BaAhHQJ7zhwo9cKR1ZS4="
|
49 |
+
},
|
50 |
+
"ep_success_buffer": {
|
51 |
+
":type:": "<class 'collections.deque'>",
|
52 |
+
":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
|
53 |
+
},
|
54 |
+
"_n_updates": 248,
|
55 |
+
"observation_space": {
|
56 |
+
":type:": "<class 'gymnasium.spaces.box.Box'>",
|
57 |
+
":serialized:": "gAWVdgIAAAAAAACMFGd5bW5hc2l1bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lIwFZHR5cGWUk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMDWJvdW5kZWRfYmVsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWCAAAAAAAAAABAQEBAQEBAZRoCIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksIhZSMAUOUdJRSlIwNYm91bmRlZF9hYm92ZZRoESiWCAAAAAAAAAABAQEBAQEBAZRoFUsIhZRoGXSUUpSMBl9zaGFwZZRLCIWUjANsb3eUaBEoliAAAAAAAAAAAAC0wgAAtMIAAKDAAACgwNsPScAAAKDAAAAAgAAAAICUaAtLCIWUaBl0lFKUjARoaWdolGgRKJYgAAAAAAAAAAAAtEIAALRCAACgQAAAoEDbD0lAAACgQAAAgD8AAIA/lGgLSwiFlGgZdJRSlIwIbG93X3JlcHKUjFtbLTkwLiAgICAgICAgLTkwLiAgICAgICAgIC01LiAgICAgICAgIC01LiAgICAgICAgIC0zLjE0MTU5MjcgIC01LgogIC0wLiAgICAgICAgIC0wLiAgICAgICBdlIwJaGlnaF9yZXBylIxTWzkwLiAgICAgICAgOTAuICAgICAgICAgNS4gICAgICAgICA1LiAgICAgICAgIDMuMTQxNTkyNyAgNS4KICAxLiAgICAgICAgIDEuICAgICAgIF2UjApfbnBfcmFuZG9tlE51Yi4=",
|
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:": "gAWV2wAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgOjApfbnBfcmFuZG9tlE51Yi4=",
|
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": 64,
|
87 |
+
"n_epochs": 4,
|
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-v2-2/policy.optimizer.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:c404de0c3eccbcc7727626f57e1f9ee8c8d7435d4b7f6cfb2cf77e757e235b4e
|
3 |
+
size 87978
|
ppo-LunarLander-v2-2/policy.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:1461dcf879f8feb28a7ce97f2a61c1954479a1786eeea0e363553e944ba43e6b
|
3 |
+
size 43634
|
ppo-LunarLander-v2-2/pytorch_variables.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:0c35cea3b2e60fb5e7e162d3592df775cd400e575a31c72f359fb9e654ab00c5
|
3 |
+
size 864
|
ppo-LunarLander-v2-2/system_info.txt
ADDED
@@ -0,0 +1,9 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
- OS: Linux-6.1.85+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Thu Jun 27 21:05:47 UTC 2024
|
2 |
+
- Python: 3.10.12
|
3 |
+
- Stable-Baselines3: 2.0.0a5
|
4 |
+
- PyTorch: 2.5.1+cu121
|
5 |
+
- GPU Enabled: False
|
6 |
+
- Numpy: 1.26.4
|
7 |
+
- Cloudpickle: 3.1.0
|
8 |
+
- Gymnasium: 0.28.1
|
9 |
+
- OpenAI Gym: 0.25.2
|
replay.mp4
ADDED
Binary file (184 kB). View file
|
|
results.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"mean_reward": 258.1823915, "std_reward": 14.500279601379502, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2025-01-13T04:30:16.132197"}
|