Commit
•
f22abeb
1
Parent(s):
4ed1ba9
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
- 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: 174.96 +/- 12.10
|
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 0x000002172C8F2F70>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x000002172C8F6040>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x000002172C8F60D0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x000002172C8F6160>", "_build": "<function ActorCriticPolicy._build at 0x000002172C8F61F0>", "forward": "<function ActorCriticPolicy.forward at 0x000002172C8F6280>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x000002172C8F6310>", "_predict": "<function ActorCriticPolicy._predict at 0x000002172C8F63A0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x000002172C8F6430>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x000002172C8F64C0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x000002172C8F6550>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x000002172C8F8140>"}, "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": 1667678697470750300, "learning_rate": 0.0003, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_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": "Windows-10-10.0.22000-SP0 10.0.22000", "Python": "3.9.13", "Stable-Baselines3": "1.6.2", "PyTorch": "1.13.0+cpu", "GPU Enabled": "False", "Numpy": "1.21.5", "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:a74164160cdb0bcf74758ab691d4ff5b6d4d1af60925c1d3b607ac04d31fbc34
|
3 |
+
size 146527
|
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 0x000002172C8F2F70>",
|
8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x000002172C8F6040>",
|
9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x000002172C8F60D0>",
|
10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x000002172C8F6160>",
|
11 |
+
"_build": "<function ActorCriticPolicy._build at 0x000002172C8F61F0>",
|
12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x000002172C8F6280>",
|
13 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x000002172C8F6310>",
|
14 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x000002172C8F63A0>",
|
15 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x000002172C8F6430>",
|
16 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x000002172C8F64C0>",
|
17 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x000002172C8F6550>",
|
18 |
+
"__abstractmethods__": "frozenset()",
|
19 |
+
"_abc_impl": "<_abc._abc_data object at 0x000002172C8F8140>"
|
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": 1667678697470750300,
|
51 |
+
"learning_rate": 0.0003,
|
52 |
+
"tensorboard_log": null,
|
53 |
+
"lr_schedule": {
|
54 |
+
":type:": "<class 'function'>",
|
55 |
+
":serialized:": "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"
|
56 |
+
},
|
57 |
+
"_last_obs": {
|
58 |
+
":type:": "<class 'numpy.ndarray'>",
|
59 |
+
":serialized:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAAG2rv76DQng/FZ18vg+COr6Spt+++4FmvgAAAAAAAAAATQA2vSnIZrofXhY6VT3zskv/mbpn2Su5AACAPwAAgD/GEDw+iDj5vJOP9jx/cDU9HYJGvui9vDwAAIA/AACAP5NJPL5ta28/bjS1O1BJkL5/+Ei8xg+lvQAAAAAAAAAAYCpNPhtA27wDnmY8FFb/uiW4Pr4nesS7AACAPwAAgD/mHou9IxVpP+7f0T16MWq+Me3jugRiBD4AAAAAAAAAAFM9Cb7mPqA//ZZxvjy7UL5ZlVa+/awkvQAAAAAAAAAA4JYfvkMnB7xyU6A7QKzuOfcqYz0ID6e6AACAPwAAgD8A4E07SIuVujb3krtCNqg33B7RuoVeYzoAAIA/AACAP4AVj72FM6u5ReYQu+ZpbbVz/a86e4YmOgAAgD8AAIA/5vdfvY+qU7roFVS7eui4tkiU5bq19HA6AACAPwAAgD8gejY+9l80vPJeFLs1Cmw5qc2ivbUWDjoAAIA/AACAP6C9BD6+xBU/oke4u4LKh774UQC9c/A8uwAAAAAAAAAAA5WSPjqyHL0WXyC79BDPORVvh75lrVI6AACAPwAAgD8VoJi+rgO/uhm5kLueM8q7jhncO7fOpbsAAAAAAAAAAACpEz1SKNa5DfcYuzHl0De+2+27Lf2PtQAAgD8AAIA/lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksQSwiGlIwBQ5R0lFKULg=="
|
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////9LAHSUYkMIeZPfopOXTECUhpRSlIwBbJRN6AOMAXSUR0B6wryMDOkddX2UKGgGaAloD0MIUrgehes5XECUhpRSlGgVTegDaBZHQHrgRnWattB1fZQoaAZoCWgPQwhSnKOOjh9WQJSGlFKUaBVN6ANoFkdAeuDoicG1QnV9lChoBmgJaA9DCCx+U1ipXEpAlIaUUpRoFU3oA2gWR0B690hwEQoTdX2UKGgGaAloD0MIbm5MT1jGVkCUhpRSlGgVTegDaBZHQHsLjWwu/UR1fZQoaAZoCWgPQwj2s1iK5HsiQJSGlFKUaBVNBgFoFkdAeyG8rI5o5HV9lChoBmgJaA9DCBk5C3vaF1pAlIaUUpRoFU3oA2gWR0B7I8efZmI1dX2UKGgGaAloD0MIzAwbZf3mEUCUhpRSlGgVTTcBaBZHQHsmhqbjLjh1fZQoaAZoCWgPQwhseeV62yRfQJSGlFKUaBVN6ANoFkdAeyiJNCZ4OnV9lChoBmgJaA9DCBGKraBp40VAlIaUUpRoFU0JAWgWR0B7KuX3QD3edX2UKGgGaAloD0MIhCwLJv6RUECUhpRSlGgVTegDaBZHQHs2/u5SWJJ1fZQoaAZoCWgPQwhW0/VE1y02QJSGlFKUaBVNIwFoFkdAe0oxPwd8zHV9lChoBmgJaA9DCJmCNc6mm15AlIaUUpRoFU3oA2gWR0B7TYIQe3hGdX2UKGgGaAloD0MIscQDyib1YECUhpRSlGgVTegDaBZHQHuVK4H5aeR1fZQoaAZoCWgPQwgBGM+goRpfQJSGlFKUaBVN6ANoFkdAe7l0wJw84nV9lChoBmgJaA9DCKEwKNNorkRAlIaUUpRoFU3oA2gWR0B7w/qhUR4AdX2UKGgGaAloD0MIGJP+Xgr3V0CUhpRSlGgVTegDaBZHQHvOfb48EFJ1fZQoaAZoCWgPQwh23zE8dkhmQJSGlFKUaBVNzQJoFkdAfBUoCdSVGHV9lChoBmgJaA9DCPvJGB9mJyRAlIaUUpRoFU0QAWgWR0B8VqGsV+I/dX2UKGgGaAloD0MIkEsceSDCK0CUhpRSlGgVTQ0BaBZHQHxfi4Bmwq11fZQoaAZoCWgPQwjerSzRWc9fQJSGlFKUaBVN6ANoFkdAfGJxA0Kqn3V9lChoBmgJaA9DCGt9kdCWVV1AlIaUUpRoFU3oA2gWR0B8iznhbW3CdX2UKGgGaAloD0MIvCAiNe0mYkCUhpRSlGgVTegDaBZHQHydYgvDgqF1fZQoaAZoCWgPQwjHSsyzkt1aQJSGlFKUaBVN6ANoFkdAfMoblijL0XV9lChoBmgJaA9DCN5Wem02VF1AlIaUUpRoFU3oA2gWR0B8zDV2A5JcdX2UKGgGaAloD0MITiUDQBWVX0CUhpRSlGgVTegDaBZHQHzO3YHxBmh1fZQoaAZoCWgPQwgST3YzozJWQJSGlFKUaBVN6ANoFkdAfNDlE7W/anV9lChoBmgJaA9DCGqHvyZr/VJAlIaUUpRoFU3oA2gWR0B800mPYFq0dX2UKGgGaAloD0MIM/rRcMpcCUCUhpRSlGgVTWEBaBZHQHzYdsnAqNJ1fZQoaAZoCWgPQwjDfeTWpLphQJSGlFKUaBVN6ANoFkdAfN7Vh1DBuXV9lChoBmgJaA9DCImV0chnNmFAlIaUUpRoFU3oA2gWR0B87aPBBRhudX2UKGgGaAloD0MIC5sBLsg9YkCUhpRSlGgVTegDaBZHQHzw/L9uP3l1fZQoaAZoCWgPQwhpOdBDbY9AwJSGlFKUaBVNHAFoFkdAfSG5KvmoznV9lChoBmgJaA9DCL74oj1evDpAlIaUUpRoFU1LAWgWR0B9LOjua4MGdX2UKGgGaAloD0MIdQXbiKflYECUhpRSlGgVTegDaBZHQH0uN/BnBcl1fZQoaAZoCWgPQwjX9nZLchZIwJSGlFKUaBVNGgFoFkdAfTAvuPV/c3V9lChoBmgJaA9DCGx7uyU50BXAlIaUUpRoFU01AWgWR0B9TKCz1K5DdX2UKGgGaAloD0MID3wMVpz+VECUhpRSlGgVTegDaBZHQH1Yxfa6BiF1fZQoaAZoCWgPQwiCx7d3DdoZQJSGlFKUaBVL72gWR0B9gem78Nx3dX2UKGgGaAloD0MI/OB86ljlGUCUhpRSlGgVTTYBaBZHQH2XVBhQWN51fZQoaAZoCWgPQwgsYW2MncAeQJSGlFKUaBVN6ANoFkdAfZn3WFvhqHV9lChoBmgJaA9DCFysqME09FhAlIaUUpRoFU3oA2gWR0B94ugkC3gDdX2UKGgGaAloD0MI0h3EzhSxYkCUhpRSlGgVTegDaBZHQH3kd7jT8YR1fZQoaAZoCWgPQwiqDU5Ev/dYQJSGlFKUaBVN6ANoFkdAfgSUS7GvOnV9lChoBmgJaA9DCG9IowInBVNAlIaUUpRoFU3oA2gWR0B+FEnRb8m8dX2UKGgGaAloD0MI0ZLH0/I0WkCUhpRSlGgVTegDaBZHQH49kRradtl1fZQoaAZoCWgPQwj8x0J0iHVgQJSGlFKUaBVN6ANoFkdAfkRJ+UhV2nV9lChoBmgJaA9DCEQy5Nh6YlRAlIaUUpRoFU3oA2gWR0B+RrwEyLyddX2UKGgGaAloD0MII0vmWN5xYECUhpRSlGgVTegDaBZHQH5OatDD0lJ1fZQoaAZoCWgPQwhhTzv8NfBgQJSGlFKUaBVN6ANoFkdAfmyxbSqlxnV9lChoBmgJaA9DCBbe5SK+ayjAlIaUUpRoFU00AWgWR0B+gkSCe2/jdX2UKGgGaAloD0MIMEllijlJYUCUhpRSlGgVTegDaBZHQH6j1TrE9+x1fZQoaAZoCWgPQwhqLjcY6kAuwJSGlFKUaBVNLAFoFkdAfq6MaCL/CXV9lChoBmgJaA9DCHgMj/2sVWRAlIaUUpRoFU3oA2gWR0B+sE5cTrVwdX2UKGgGaAloD0MIhGdCk8SSsj+UhpRSlGgVTUsBaBZHQH7AJjx0+1V1fZQoaAZoCWgPQwiVtyOcFtReQJSGlFKUaBVN6ANoFkdAftSL7oB7u3V9lChoBmgJaA9DCJo/prVpZV5AlIaUUpRoFU3oA2gWR0B+49o7FKkEdX2UKGgGaAloD0MI8BZIUHyaYkCUhpRSlGgVTegDaBZHQH8KtrCWNWF1fZQoaAZoCWgPQwgY6xuY3CgawJSGlFKUaBVNJAFoFkdAfwxI1LrX2HV9lChoBmgJaA9DCOPfZ1w4g1RAlIaUUpRoFU3oA2gWR0B/H0gDA8B/dX2UKGgGaAloD0MI/TIYIxKLXECUhpRSlGgVTegDaBZHQH8jJsTFl051fZQoaAZoCWgPQwjBrFCk+/EqQJSGlFKUaBVNIQFoFkdAfyYMURFqjHV9lChoBmgJaA9DCHqlLEMcUFtAlIaUUpRoFU3oA2gWR0B/Nq3nZCfIdX2UKGgGaAloD0MIdQKaCBudYUCUhpRSlGgVTegDaBZHQH84PXPJJXh1fZQoaAZoCWgPQwjD19e61IgdwJSGlFKUaBVNNQFoFkdAf3AIo3JgcHV9lChoBmgJaA9DCHL6er7mM2BAlIaUUpRoFU3oA2gWR0B/hb2oNutPdX2UKGgGaAloD0MIUpyjjo5rGUCUhpRSlGgVTU4BaBZHQH+ei17Y02t1fZQoaAZoCWgPQwhgHccPlXoywJSGlFKUaBVNXgFoFkdAf7JJfpljE3V9lChoBmgJaA9DCE5hpYKKblxAlIaUUpRoFU3oA2gWR0B/ttbGFSKndX2UKGgGaAloD0MIObcJ98qKWUCUhpRSlGgVTegDaBZHQH+6uCkGiYd1fZQoaAZoCWgPQwg0SSwpd38HQJSGlFKUaBVNOgFoFkdAf7zEcbR4QnV9lChoBmgJaA9DCFnfwORGg15AlIaUUpRoFU3oA2gWR0B/3GLFXJYDdX2UKGgGaAloD0MIxccnZGdDYUCUhpRSlGgVTegDaBZHQH/tRvFWGRF1fZQoaAZoCWgPQwjH9IQlHvxUQJSGlFKUaBVN6ANoFkdAgAiS6+WWyHV9lChoBmgJaA9DCN5Zu+3CLmFAlIaUUpRoFU3oA2gWR0CACWuzQeFMdX2UKGgGaAloD0MI38X7cft1XUCUhpRSlGgVTegDaBZHQIAe4xBVuJl1fZQoaAZoCWgPQwhzEd+JWZ9jQJSGlFKUaBVN6ANoFkdAgC7w2VE/jnV9lChoBmgJaA9DCJzDtdrDfldAlIaUUpRoFU3oA2gWR0CAOVtWuHN5dX2UKGgGaAloD0MIu0bLgR5+XkCUhpRSlGgVTegDaBZHQIA6ngFX7tR1fZQoaAZoCWgPQwh39pUH6TlcQJSGlFKUaBVN6ANoFkdAgEJQFTvRZ3V9lChoBmgJaA9DCCEeiZenbl1AlIaUUpRoFU3oA2gWR0CARdTZQHiWdX2UKGgGaAloD0MIs193uvO8XECUhpRSlGgVTegDaBZHQIBsXXEqDsd1fZQoaAZoCWgPQwiKPh9lRBhiQJSGlFKUaBVN6ANoFkdAgHcfaxoqTnV9lChoBmgJaA9DCDVG66hqkilAlIaUUpRoFU03AWgWR0CAfSfPHDJmdX2UKGgGaAloD0MITRQhdTtfXECUhpRSlGgVTegDaBZHQIB/YbCJoCd1fZQoaAZoCWgPQwg/O+C6Yi9dQJSGlFKUaBVN6ANoFkdAgIBmLk0aZXV9lChoBmgJaA9DCFJ+Uu1TxWBAlIaUUpRoFU3oA2gWR0CAgeiA2AG0dX2UKGgGaAloD0MIs3kcBvMfWkCUhpRSlGgVTegDaBZHQICCtAPd2xJ1fZQoaAZoCWgPQwhxqyAGulYDQJSGlFKUaBVL8GgWR0CAh4NhmXgMdX2UKGgGaAloD0MI4NdIEgRMYECUhpRSlGgVTegDaBZHQICObK9wm3R1fZQoaAZoCWgPQwgsSZ7r+8djQJSGlFKUaBVN6ANoFkdAgJWSMcZLqXV9lChoBmgJaA9DCHS366UpNjbAlIaUUpRoFU1EAWgWR0CAoRp8neBQdX2UKGgGaAloD0MIbhPulXnDZECUhpRSlGgVTegDaBZHQICj+VLSNOx1fZQoaAZoCWgPQwjeVQ+YBwFhQJSGlFKUaBVN6ANoFkdAgKSA3974SHV9lChoBmgJaA9DCNUI/Uy9FVxAlIaUUpRoFU3oA2gWR0CAtYctoSL7dX2UKGgGaAloD0MIkgVM4NaVXUCUhpRSlGgVTegDaBZHQIDTTl3hXKd1fZQoaAZoCWgPQwjmWN5VD39fQJSGlFKUaBVN6ANoFkdAgOUMd92HL3V9lChoBmgJaA9DCLFvJxHhDzbAlIaUUpRoFU1LAWgWR0CA5RrhR64UdX2UKGgGaAloD0MI++k/a34aW0CUhpRSlGgVTegDaBZHQIDtFZzPrv91fZQoaAZoCWgPQwiZSGk2j99cQJSGlFKUaBVN6ANoFkdAgO8KaXrt3XVlLg=="
|
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:e642cdeadffa5055d0e65f3561861e06c0ed8a3efe6ad84469df0d3155be1f94
|
3 |
+
size 87545
|
ppo-LunarLander-v2/policy.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:f8cd04219da38550ee0020a4e7cb1a9c96e21a28e1ded3306d01f0988461b534
|
3 |
+
size 43073
|
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: Windows-10-10.0.22000-SP0 10.0.22000
|
2 |
+
Python: 3.9.13
|
3 |
+
Stable-Baselines3: 1.6.2
|
4 |
+
PyTorch: 1.13.0+cpu
|
5 |
+
GPU Enabled: False
|
6 |
+
Numpy: 1.21.5
|
7 |
+
Gym: 0.21.0
|
results.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"mean_reward": 174.96404776462748, "std_reward": 12.10162676341215, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-11-05T21:24:20.508335"}
|