Commit
•
2f7d62e
1
Parent(s):
4dfe7b9
Upload PPO LunarLander-v2 trained agent
Browse files- README.md +37 -0
- config.json +1 -0
- ppo-LunarLander-v2.zip +3 -0
- ppo-LunarLander-v2/_stable_baselines3_version +1 -0
- ppo-LunarLander-v2/data +94 -0
- ppo-LunarLander-v2/policy.optimizer.pth +3 -0
- ppo-LunarLander-v2/policy.pth +3 -0
- ppo-LunarLander-v2/pytorch_variables.pth +3 -0
- ppo-LunarLander-v2/system_info.txt +7 -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: 68.54 +/- 89.22
|
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 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 0x7f3c3bd810d0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f3c3bd81160>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f3c3bd811f0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f3c3bd81280>", "_build": "<function ActorCriticPolicy._build at 0x7f3c3bd81310>", "forward": "<function ActorCriticPolicy.forward at 0x7f3c3bd813a0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f3c3bd81430>", "_predict": "<function ActorCriticPolicy._predict at 0x7f3c3bd814c0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f3c3bd81550>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f3c3bd815e0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f3c3bd81670>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f3c3bd7c3f0>"}, "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": 16, "num_timesteps": 507904, "_total_timesteps": 500000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1667997810858671134, "learning_rate": 0.0003, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "gAWVwQIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwNX2J1aWx0aW5fdHlwZZSTlIwKTGFtYmRhVHlwZZSFlFKUKGgCjAhDb2RlVHlwZZSFlFKUKEsBSwBLAEsBSwFLE0MEiABTAJROhZQpjAFflIWUjEgvb3B0L2NvbmRhL2xpYi9weXRob24zLjgvc2l0ZS1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUjARmdW5jlEuAQwIAAZSMA3ZhbJSFlCl0lFKUfZQojAtfX3BhY2thZ2VfX5SMGHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbpSMCF9fbmFtZV9flIwec3RhYmxlX2Jhc2VsaW5lczMuY29tbW9uLnV0aWxzlIwIX19maWxlX1+UjEgvb3B0L2NvbmRhL2xpYi9weXRob24zLjgvc2l0ZS1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUdU5OaACMEF9tYWtlX2VtcHR5X2NlbGyUk5QpUpSFlHSUUpSMHGNsb3VkcGlja2xlLmNsb3VkcGlja2xlX2Zhc3SUjBJfZnVuY3Rpb25fc2V0c3RhdGWUk5RoIH2UfZQoaBdoDowMX19xdWFsbmFtZV9flIwZY29uc3RhbnRfZm4uPGxvY2Fscz4uZnVuY5SMD19fYW5ub3RhdGlvbnNfX5R9lIwOX19rd2RlZmF1bHRzX1+UTowMX19kZWZhdWx0c19flE6MCl9fbW9kdWxlX1+UaBiMB19fZG9jX1+UTowLX19jbG9zdXJlX1+UaACMCl9tYWtlX2NlbGyUk5RHPzOpKjBVMmGFlFKUhZSMF19jbG91ZHBpY2tsZV9zdWJtb2R1bGVzlF2UjAtfX2dsb2JhbHNfX5R9lHWGlIZSMC4="}, "_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, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 124, "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, "system_info": {"OS": "Linux-5.4.0-124-generic-x86_64-with-glibc2.10 #140-Ubuntu SMP Thu Aug 4 02:23:37 UTC 2022", "Python": "3.8.13", "Stable-Baselines3": "1.6.2", "PyTorch": "1.12.0a0+bd13bc6", "GPU Enabled": "True", "Numpy": "1.22.3", "Gym": "0.21.0"}}
|
ppo-LunarLander-v2.zip
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:127c9522f0588c2cd6afa69fdc0d438e04baab7c7da549f6f812ac9d47529431
|
3 |
+
size 147164
|
ppo-LunarLander-v2/_stable_baselines3_version
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
1.6.2
|
ppo-LunarLander-v2/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 0x7f3c3bd810d0>",
|
8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f3c3bd81160>",
|
9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f3c3bd811f0>",
|
10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f3c3bd81280>",
|
11 |
+
"_build": "<function ActorCriticPolicy._build at 0x7f3c3bd81310>",
|
12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x7f3c3bd813a0>",
|
13 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f3c3bd81430>",
|
14 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x7f3c3bd814c0>",
|
15 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f3c3bd81550>",
|
16 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f3c3bd815e0>",
|
17 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7f3c3bd81670>",
|
18 |
+
"__abstractmethods__": "frozenset()",
|
19 |
+
"_abc_impl": "<_abc_data object at 0x7f3c3bd7c3f0>"
|
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": 16,
|
45 |
+
"num_timesteps": 507904,
|
46 |
+
"_total_timesteps": 500000,
|
47 |
+
"_num_timesteps_at_start": 0,
|
48 |
+
"seed": null,
|
49 |
+
"action_noise": null,
|
50 |
+
"start_time": 1667997810858671134,
|
51 |
+
"learning_rate": 0.0003,
|
52 |
+
"tensorboard_log": null,
|
53 |
+
"lr_schedule": {
|
54 |
+
":type:": "<class 'function'>",
|
55 |
+
":serialized:": "gAWVwQIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwNX2J1aWx0aW5fdHlwZZSTlIwKTGFtYmRhVHlwZZSFlFKUKGgCjAhDb2RlVHlwZZSFlFKUKEsBSwBLAEsBSwFLE0MEiABTAJROhZQpjAFflIWUjEgvb3B0L2NvbmRhL2xpYi9weXRob24zLjgvc2l0ZS1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUjARmdW5jlEuAQwIAAZSMA3ZhbJSFlCl0lFKUfZQojAtfX3BhY2thZ2VfX5SMGHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbpSMCF9fbmFtZV9flIwec3RhYmxlX2Jhc2VsaW5lczMuY29tbW9uLnV0aWxzlIwIX19maWxlX1+UjEgvb3B0L2NvbmRhL2xpYi9weXRob24zLjgvc2l0ZS1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUdU5OaACMEF9tYWtlX2VtcHR5X2NlbGyUk5QpUpSFlHSUUpSMHGNsb3VkcGlja2xlLmNsb3VkcGlja2xlX2Zhc3SUjBJfZnVuY3Rpb25fc2V0c3RhdGWUk5RoIH2UfZQoaBdoDowMX19xdWFsbmFtZV9flIwZY29uc3RhbnRfZm4uPGxvY2Fscz4uZnVuY5SMD19fYW5ub3RhdGlvbnNfX5R9lIwOX19rd2RlZmF1bHRzX1+UTowMX19kZWZhdWx0c19flE6MCl9fbW9kdWxlX1+UaBiMB19fZG9jX1+UTowLX19jbG9zdXJlX1+UaACMCl9tYWtlX2NlbGyUk5RHPzOpKjBVMmGFlFKUhZSMF19jbG91ZHBpY2tsZV9zdWJtb2R1bGVzlF2UjAtfX2dsb2JhbHNfX5R9lHWGlIZSMC4="
|
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:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="
|
64 |
+
},
|
65 |
+
"_last_original_obs": null,
|
66 |
+
"_episode_num": 0,
|
67 |
+
"use_sde": false,
|
68 |
+
"sde_sample_freq": -1,
|
69 |
+
"_current_progress_remaining": -0.015808000000000044,
|
70 |
+
"ep_info_buffer": {
|
71 |
+
":type:": "<class 'collections.deque'>",
|
72 |
+
":serialized:": "gAWVfxAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMI9FMcB97hYECUhpRSlIwBbJRN6AOMAXSUR0D1eIXXJ5midX2UKGgGaAloD0MIaTUk7rGnW0CUhpRSlGgVTegDaBZHQPV4mXDUExJ1fZQoaAZoCWgPQwhbXrneNr5eQJSGlFKUaBVN6ANoFkdA9XiZ7YkE93V9lChoBmgJaA9DCCBDxw4qplZAlIaUUpRoFU3oA2gWR0D1eKojh1kldX2UKGgGaAloD0MId2hYjLrmKsCUhpRSlGgVTR4BaBZHQPV4tvZ8KHB1fZQoaAZoCWgPQwhjYvNx7e5hQJSGlFKUaBVNEQJoFkdA9XjHIPoV23V9lChoBmgJaA9DCN18I7rn821AlIaUUpRoFU0jAWgWR0D1eMnZVGTcdX2UKGgGaAloD0MILH++LVijWECUhpRSlGgVTegDaBZHQPV4yhbwBo51fZQoaAZoCWgPQwjh05y8SANgQJSGlFKUaBVN6ANoFkdA9XlibqIJq3V9lChoBmgJaA9DCKFl3T8WoibAlIaUUpRoFU0nAWgWR0D1eWTMtK7JdX2UKGgGaAloD0MIho4dVOLQW0CUhpRSlGgVTegDaBZHQPV5d7mQr+Z1fZQoaAZoCWgPQwjhXpm36oBYQJSGlFKUaBVN6ANoFkdA9Xl7fJ7swHV9lChoBmgJaA9DCJKWytsRMFtAlIaUUpRoFU3oA2gWR0D1eX5x3FDOdX2UKGgGaAloD0MIHo1D/S5sXECUhpRSlGgVTegDaBZHQPV5palWOp91fZQoaAZoCWgPQwhdxeI3BedhQJSGlFKUaBVNHQJoFkdA9Xm80QTVUnV9lChoBmgJaA9DCL9k48EWE11AlIaUUpRoFU3oA2gWR0D1ecPWyC4CdX2UKGgGaAloD0MIQbeXNEbaX0CUhpRSlGgVTegDaBZHQPV5zkDGLk11fZQoaAZoCWgPQwit+IbCZxNaQJSGlFKUaBVN6ANoFkdA9XnQZAY51nV9lChoBmgJaA9DCPQ2NjtSzl1AlIaUUpRoFU3oA2gWR0D1ee6/KhcrdX2UKGgGaAloD0MIiITv/Q0tVkCUhpRSlGgVTegDaBZHQPV6B/+OwPl1fZQoaAZoCWgPQwhPzeUGQwRZQJSGlFKUaBVN6ANoFkdA9XoaVXzUZ3V9lChoBmgJaA9DCAb2mEhpnGVAlIaUUpRoFU3oA2gWR0D1ejeoxpL3dX2UKGgGaAloD0MIn5Cdt7HvWECUhpRSlGgVTegDaBZHQPV6OqV2Rq51fZQoaAZoCWgPQwgX9N4YAhVRQJSGlFKUaBVN6ANoFkdA9Xo68189fXV9lChoBmgJaA9DCAH76NSVC01AlIaUUpRoFU3oA2gWR0D1evNe9SMtdX2UKGgGaAloD0MINxjqsMKNLcCUhpRSlGgVTR8BaBZHQPV687w7T2F1fZQoaAZoCWgPQwjQtwVLdRhTQJSGlFKUaBVN6ANoFkdA9Xr2ynpB5XV9lChoBmgJaA9DCDifOlYp8llAlIaUUpRoFU3oA2gWR0D1ew3cuanadX2UKGgGaAloD0MIwHebN04sWkCUhpRSlGgVTegDaBZHQPV7EVrl/6R1fZQoaAZoCWgPQwhLW1zjM1VXQJSGlFKUaBVN6ANoFkdA9XsT+GTLXHV9lChoBmgJaA9DCCkHswkwYEjAlIaUUpRoFU0dAWgWR0D1eyJxOLzgdX2UKGgGaAloD0MIc7nBUIeFOsCUhpRSlGgVTQsBaBZHQPV7LmilBQh1fZQoaAZoCWgPQwhxdQDEXWEzQJSGlFKUaBVNFQFoFkdA9XsyvldTpHV9lChoBmgJaA9DCBDpt68DcWVAlIaUUpRoFU3oA2gWR0D1ezSbPQfIdX2UKGgGaAloD0MIt9EA3gLIX0CUhpRSlGgVTegDaBZHQPV7RxKODJ51fZQoaAZoCWgPQwhINez3xN1YQJSGlFKUaBVN6ANoFkdA9XtMoomXxHV9lChoBmgJaA9DCFQfSN45BGFAlIaUUpRoFU3oA2gWR0D1e1VAMlTndX2UKGgGaAloD0MI1eqrqwI6V0CUhpRSlGgVTegDaBZHQPV7VwHnln11fZQoaAZoCWgPQwiocW9+w+ZMQJSGlFKUaBVL7WgWR0D1e15FotcwdX2UKGgGaAloD0MIr1+wG7a1JMCUhpRSlGgVTQcBaBZHQPV7ZtT3qRl1fZQoaAZoCWgPQwgK1jibDspiQJSGlFKUaBVN6ANoFkdA9XtwNJBgNXV9lChoBmgJaA9DCL1RK0zf3VxAlIaUUpRoFU3oA2gWR0D1e5lsXSBtdX2UKGgGaAloD0MIMEeP39u3aUCUhpRSlGgVTZUCaBZHQPV7rLWoWHl1fZQoaAZoCWgPQwiBmIQLeQtbQJSGlFKUaBVN6ANoFkdA9Xu3zl1bJXV9lChoBmgJaA9DCL9jeOxn21lAlIaUUpRoFU3oA2gWR0D1e7rND+irdX2UKGgGaAloD0MIWTZzSGqVV0CUhpRSlGgVTegDaBZHQPV7zdmz0H11fZQoaAZoCWgPQwgIVtXL75ldQJSGlFKUaBVN6ANoFkdA9XypxqO94HV9lChoBmgJaA9DCKUvhJz3815AlIaUUpRoFU3oA2gWR0D1fK3uJUHZdX2UKGgGaAloD0MIE36pnzcnY0CUhpRSlGgVTegDaBZHQPV8sRHqeK91fZQoaAZoCWgPQwhS0y6mGVZpQJSGlFKUaBVNSAJoFkdA9Xyy9+Xqq3V9lChoBmgJaA9DCEhS0sNQVmRAlIaUUpRoFU3oA2gWR0D1fNZldkaudX2UKGgGaAloD0MIoiWPp2UkYECUhpRSlGgVTegDaBZHQPV87GlN1yN1fZQoaAZoCWgPQwhaaOc0CyxaQJSGlFKUaBVN6ANoFkdA9Xzy1pfx+nV9lChoBmgJaA9DCBmNfF7xtGFAlIaUUpRoFU3oA2gWR0D1fPz3IuGsdX2UKGgGaAloD0MITwXc8/z3X0CUhpRSlGgVTegDaBZHQPV8/vZDiOx1fZQoaAZoCWgPQwiifazgNxRgQJSGlFKUaBVN6ANoFkdA9X0HitFKCnV9lChoBmgJaA9DCKBQTx+BvFtAlIaUUpRoFU3oA2gWR0D1fRyrs0HhdX2UKGgGaAloD0MIGXYYk35aYECUhpRSlGgVTegDaBZHQPV9SXhaTwF1fZQoaAZoCWgPQwhcBMb6BtVZQJSGlFKUaBVN6ANoFkdA9X1cQ4bS7XV9lChoBmgJaA9DCJhp+1dW4VRAlIaUUpRoFU3oA2gWR0D1fWcb1yvLdX2UKGgGaAloD0MIjbRU3o4EV0CUhpRSlGgVTegDaBZHQPV9aew2VFB1fZQoaAZoCWgPQwjryfyjbypiQJSGlFKUaBVNzANoFkdA9X11Jiy6c3V9lChoBmgJaA9DCH+ismFNSlZAlIaUUpRoFU3oA2gWR0D1flSKlHjIdX2UKGgGaAloD0MIIjXtYhrgY0CUhpRSlGgVTegDaBZHQPV+WhelbeN1fZQoaAZoCWgPQwg6zm3CPR1hQJSGlFKUaBVN6ANoFkdA9X5dlGwzL3V9lChoBmgJaA9DCFddh2pK5lNAlIaUUpRoFU3oA2gWR0D1fl+K/EfldX2UKGgGaAloD0MIWRmNfF4TT0CUhpRSlGgVTegDaBZHQPV+gkCtA9p1fZQoaAZoCWgPQwh2UfTAx4AlQJSGlFKUaBVL4mgWR0D1fo5akyk9dX2UKGgGaAloD0MIDHiZYaPNXkCUhpRSlGgVTegDaBZHQPV+lm43FUB1fZQoaAZoCWgPQwjZ690f75FVQJSGlFKUaBVN6ANoFkdA9X6caQV9GHV9lChoBmgJaA9DCBCxwcJJ0kNAlIaUUpRoFU3oA2gWR0D1fqWwyZa3dX2UKGgGaAloD0MIVRLZB1kJXUCUhpRSlGgVTegDaBZHQPV+p4/FBIF1fZQoaAZoCWgPQwgRHm0csd5UQJSGlFKUaBVN6ANoFkdA9X6vnCj1w3V9lChoBmgJaA9DCAyuuaP/50xAlIaUUpRoFU3oA2gWR0D1fsOozeoDdX2UKGgGaAloD0MI6+Bgb2IPXUCUhpRSlGgVTegDaBZHQPV+8w4ZMtd1fZQoaAZoCWgPQwj5MHvZdpVYQJSGlFKUaBVN6ANoFkdA9X8Hb6P8ynV9lChoBmgJaA9DCMEdqFMe4WJAlIaUUpRoFU3oA2gWR0D1fxLMK1G9dX2UKGgGaAloD0MIlrTiGwowWkCUhpRSlGgVTegDaBZHQPV/Fc7W/ah1fZQoaAZoCWgPQwgu5ueGptFdQJSGlFKUaBVN6ANoFkdA9X8hqsdT53V9lChoBmgJaA9DCCXs20lE22BAlIaUUpRoFU3oA2gWR0D1f/8A5aNddX2UKGgGaAloD0MId/cA3ZctY0CUhpRSlGgVTegDaBZHQPWABIU7CBR1fZQoaAZoCWgPQwje5SK+ky9kQJSGlFKUaBVN6ANoFkdA9YAL5Zr57HV9lChoBmgJaA9DCG7A54cRhldAlIaUUpRoFU3oA2gWR0D1gDT7iyY5dX2UKGgGaAloD0MIr1+wGzYeYUCUhpRSlGgVTegDaBZHQPWAQ/LSuyN1fZQoaAZoCWgPQwh5ILJIE7VcQJSGlFKUaBVN6ANoFkdA9YBMzz7MxHV9lChoBmgJaA9DCFkxXB0AE1xAlIaUUpRoFU3oA2gWR0D1gFNZk079dX2UKGgGaAloD0MIt+ulKQLrYUCUhpRSlGgVTegDaBZHQPWAXWM85jp1fZQoaAZoCWgPQwg+Qs2QKppYQJSGlFKUaBVN6ANoFkdA9YBfc0tRN3V9lChoBmgJaA9DCNEhcCTQOVxAlIaUUpRoFU3oA2gWR0D1gGh3Ux20dX2UKGgGaAloD0MI3NRA87kKZ0CUhpRSlGgVTZQBaBZHQPWAb+h7E511fZQoaAZoCWgPQwiM3NPVHehhQJSGlFKUaBVN6ANoFkdA9YB+SEL6UXV9lChoBmgJaA9DCCZxVkRNfDVAlIaUUpRoFU01AWgWR0D1gKlzz3AVdX2UKGgGaAloD0MIguZz7nYcYECUhpRSlGgVTegDaBZHQPWArmcd5pt1fZQoaAZoCWgPQwiwPEhPkas7wJSGlFKUaBVNCQFoFkdA9YCx4R28qXV9lChoBmgJaA9DCCU/4lcsDmBAlIaUUpRoFU3oA2gWR0D1gMKpGnXNdX2UKGgGaAloD0MIdO52vTRPRECUhpRSlGgVTTUBaBZHQPWAzX06HTJ1fZQoaAZoCWgPQwggKo2Y2StfQJSGlFKUaBVN6ANoFkdA9YDNg/s3Q3V9lChoBmgJaA9DCHyA7suZ5V5AlIaUUpRoFU3oA2gWR0D1gNBJ17pndX2UKGgGaAloD0MIQ8cOKvHlYUCUhpRSlGgVTegDaBZHQPWA2zRTjvN1fZQoaAZoCWgPQwj5odKIGdhiQJSGlFKUaBVNPgJoFkdA9YDeG1lXinVlLg=="
|
73 |
+
},
|
74 |
+
"ep_success_buffer": {
|
75 |
+
":type:": "<class 'collections.deque'>",
|
76 |
+
":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
|
77 |
+
},
|
78 |
+
"_n_updates": 124,
|
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": 4,
|
87 |
+
"clip_range": {
|
88 |
+
":type:": "<class 'function'>",
|
89 |
+
":serialized:": "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"
|
90 |
+
},
|
91 |
+
"clip_range_vf": null,
|
92 |
+
"normalize_advantage": true,
|
93 |
+
"target_kl": null
|
94 |
+
}
|
ppo-LunarLander-v2/policy.optimizer.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:f5b823a950b3a510c382bd2d4b5193c07767c86d8589dad7a3bd9182e42fa9e2
|
3 |
+
size 87865
|
ppo-LunarLander-v2/policy.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:108e95aab632a6c8bccda5928f8279327fce96683e9194e63b4980be17ba8a98
|
3 |
+
size 43201
|
ppo-LunarLander-v2/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/system_info.txt
ADDED
@@ -0,0 +1,7 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
OS: Linux-5.4.0-124-generic-x86_64-with-glibc2.10 #140-Ubuntu SMP Thu Aug 4 02:23:37 UTC 2022
|
2 |
+
Python: 3.8.13
|
3 |
+
Stable-Baselines3: 1.6.2
|
4 |
+
PyTorch: 1.12.0a0+bd13bc6
|
5 |
+
GPU Enabled: True
|
6 |
+
Numpy: 1.22.3
|
7 |
+
Gym: 0.21.0
|
replay.mp4
ADDED
Binary file (259 kB). View file
|
|
results.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"mean_reward": 68.5390582682422, "std_reward": 89.22116245958337, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-11-09T14:45:31.053166"}
|