Initial commit
Browse files- .gitattributes +1 -0
- README.md +28 -0
- a2c-HalfCheetahBulletEnv-v0.zip +3 -0
- a2c-HalfCheetahBulletEnv-v0/_stable_baselines3_version +1 -0
- a2c-HalfCheetahBulletEnv-v0/data +105 -0
- a2c-HalfCheetahBulletEnv-v0/policy.optimizer.pth +3 -0
- a2c-HalfCheetahBulletEnv-v0/policy.pth +3 -0
- a2c-HalfCheetahBulletEnv-v0/pytorch_variables.pth +3 -0
- a2c-HalfCheetahBulletEnv-v0/system_info.txt +7 -0
- config.json +1 -0
- replay.mp4 +3 -0
- results.json +1 -0
.gitattributes
CHANGED
@@ -29,3 +29,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
|
|
29 |
*.zip filter=lfs diff=lfs merge=lfs -text
|
30 |
*.zstandard filter=lfs diff=lfs merge=lfs -text
|
31 |
*tfevents* filter=lfs diff=lfs merge=lfs -text
|
|
|
|
29 |
*.zip filter=lfs diff=lfs merge=lfs -text
|
30 |
*.zstandard filter=lfs diff=lfs merge=lfs -text
|
31 |
*tfevents* filter=lfs diff=lfs merge=lfs -text
|
32 |
+
*.mp4 filter=lfs diff=lfs merge=lfs -text
|
README.md
ADDED
@@ -0,0 +1,28 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
---
|
2 |
+
library_name: stable-baselines3
|
3 |
+
tags:
|
4 |
+
- HalfCheetahBulletEnv-v0
|
5 |
+
- deep-reinforcement-learning
|
6 |
+
- reinforcement-learning
|
7 |
+
- stable-baselines3
|
8 |
+
model-index:
|
9 |
+
- name: A2C
|
10 |
+
results:
|
11 |
+
- metrics:
|
12 |
+
- type: mean_reward
|
13 |
+
value: 1498.70 +/- 811.27
|
14 |
+
name: mean_reward
|
15 |
+
task:
|
16 |
+
type: reinforcement-learning
|
17 |
+
name: reinforcement-learning
|
18 |
+
dataset:
|
19 |
+
name: HalfCheetahBulletEnv-v0
|
20 |
+
type: HalfCheetahBulletEnv-v0
|
21 |
+
---
|
22 |
+
|
23 |
+
# **A2C** Agent playing **HalfCheetahBulletEnv-v0**
|
24 |
+
This is a trained model of a **A2C** agent playing **HalfCheetahBulletEnv-v0** using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
|
25 |
+
|
26 |
+
## Usage (with Stable-baselines3)
|
27 |
+
TODO: Add your code
|
28 |
+
|
a2c-HalfCheetahBulletEnv-v0.zip
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:92b3cf6e1bee8759d3aa5ce12e03a9310d673d2f34074d3ae0eefc47e0d300ab
|
3 |
+
size 121752
|
a2c-HalfCheetahBulletEnv-v0/_stable_baselines3_version
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
1.5.0
|
a2c-HalfCheetahBulletEnv-v0/data
ADDED
@@ -0,0 +1,105 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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 0x7f29c7aff3a0>",
|
8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f29c7aff430>",
|
9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f29c7aff4c0>",
|
10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f29c7aff550>",
|
11 |
+
"_build": "<function ActorCriticPolicy._build at 0x7f29c7aff5e0>",
|
12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x7f29c7aff670>",
|
13 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f29c7aff700>",
|
14 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x7f29c7aff790>",
|
15 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f29c7aff820>",
|
16 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f29c7aff8b0>",
|
17 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7f29c7aff940>",
|
18 |
+
"__abstractmethods__": "frozenset()",
|
19 |
+
"_abc_impl": "<_abc._abc_data object at 0x7f29c7cc8e00>"
|
20 |
+
},
|
21 |
+
"verbose": 1,
|
22 |
+
"policy_kwargs": {
|
23 |
+
":type:": "<class 'dict'>",
|
24 |
+
":serialized:": "gAWVowAAAAAAAAB9lCiMDGxvZ19zdGRfaW5pdJRK/v///4wKb3J0aG9faW5pdJSJjA9vcHRpbWl6ZXJfY2xhc3OUjBN0b3JjaC5vcHRpbS5ybXNwcm9wlIwHUk1TcHJvcJSTlIwQb3B0aW1pemVyX2t3YXJnc5R9lCiMBWFscGhhlEc/764UeuFHrowDZXBzlEc+5Pi1iONo8YwMd2VpZ2h0X2RlY2F5lEsAdXUu",
|
25 |
+
"log_std_init": -2,
|
26 |
+
"ortho_init": false,
|
27 |
+
"optimizer_class": "<class 'torch.optim.rmsprop.RMSprop'>",
|
28 |
+
"optimizer_kwargs": {
|
29 |
+
"alpha": 0.99,
|
30 |
+
"eps": 1e-05,
|
31 |
+
"weight_decay": 0
|
32 |
+
}
|
33 |
+
},
|
34 |
+
"observation_space": {
|
35 |
+
":type:": "<class 'gym.spaces.box.Box'>",
|
36 |
+
":serialized:": "gAWVUwIAAAAAAACMDmd5bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lGgFk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMBl9zaGFwZZRLGoWUjANsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWaAAAAAAAAAAAAID/AACA/wAAgP8AAID/AACA/wAAgP8AAID/AACA/wAAgP8AAID/AACA/wAAgP8AAID/AACA/wAAgP8AAID/AACA/wAAgP8AAID/AACA/wAAgP8AAID/AACA/wAAgP8AAID/AACA/5RoCksahZSMAUOUdJRSlIwEaGlnaJRoEiiWaAAAAAAAAAAAAIB/AACAfwAAgH8AAIB/AACAfwAAgH8AAIB/AACAfwAAgH8AAIB/AACAfwAAgH8AAIB/AACAfwAAgH8AAIB/AACAfwAAgH8AAIB/AACAfwAAgH8AAIB/AACAfwAAgH8AAIB/AACAf5RoCksahZRoFXSUUpSMDWJvdW5kZWRfYmVsb3eUaBIolhoAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUaAeMAmIxlImIh5RSlChLA4wBfJROTk5K/////0r/////SwB0lGJLGoWUaBV0lFKUjA1ib3VuZGVkX2Fib3ZllGgSKJYaAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAlGghSxqFlGgVdJRSlIwKX25wX3JhbmRvbZROdWIu",
|
37 |
+
"dtype": "float32",
|
38 |
+
"_shape": [
|
39 |
+
26
|
40 |
+
],
|
41 |
+
"low": "[-inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf\n -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf]",
|
42 |
+
"high": "[inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf\n inf inf inf inf inf inf inf inf]",
|
43 |
+
"bounded_below": "[False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False]",
|
44 |
+
"bounded_above": "[False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False]",
|
45 |
+
"_np_random": null
|
46 |
+
},
|
47 |
+
"action_space": {
|
48 |
+
":type:": "<class 'gym.spaces.box.Box'>",
|
49 |
+
":serialized:": "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",
|
50 |
+
"dtype": "float32",
|
51 |
+
"_shape": [
|
52 |
+
6
|
53 |
+
],
|
54 |
+
"low": "[-1. -1. -1. -1. -1. -1.]",
|
55 |
+
"high": "[1. 1. 1. 1. 1. 1.]",
|
56 |
+
"bounded_below": "[ True True True True True True]",
|
57 |
+
"bounded_above": "[ True True True True True True]",
|
58 |
+
"_np_random": null
|
59 |
+
},
|
60 |
+
"n_envs": 8,
|
61 |
+
"num_timesteps": 0,
|
62 |
+
"_total_timesteps": 2000000,
|
63 |
+
"_num_timesteps_at_start": 0,
|
64 |
+
"seed": null,
|
65 |
+
"action_noise": null,
|
66 |
+
"start_time": 1659352750.6474247,
|
67 |
+
"learning_rate": 0.00096,
|
68 |
+
"tensorboard_log": "./tensorboard",
|
69 |
+
"lr_schedule": {
|
70 |
+
":type:": "<class 'function'>",
|
71 |
+
":serialized:": "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"
|
72 |
+
},
|
73 |
+
"_last_obs": {
|
74 |
+
":type:": "<class 'numpy.ndarray'>",
|
75 |
+
":serialized:": "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"
|
76 |
+
},
|
77 |
+
"_last_episode_starts": {
|
78 |
+
":type:": "<class 'numpy.ndarray'>",
|
79 |
+
":serialized:": "gAWVewAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYIAAAAAAAAAAEBAQEBAQEBlIwFbnVtcHmUjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksIhZSMAUOUdJRSlC4="
|
80 |
+
},
|
81 |
+
"_last_original_obs": {
|
82 |
+
":type:": "<class 'numpy.ndarray'>",
|
83 |
+
":serialized:": "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"
|
84 |
+
},
|
85 |
+
"_episode_num": 0,
|
86 |
+
"use_sde": true,
|
87 |
+
"sde_sample_freq": -1,
|
88 |
+
"_current_progress_remaining": 0.0,
|
89 |
+
"ep_info_buffer": {
|
90 |
+
":type:": "<class 'collections.deque'>",
|
91 |
+
":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
|
92 |
+
},
|
93 |
+
"ep_success_buffer": {
|
94 |
+
":type:": "<class 'collections.deque'>",
|
95 |
+
":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
|
96 |
+
},
|
97 |
+
"_n_updates": 156250,
|
98 |
+
"n_steps": 8,
|
99 |
+
"gamma": 0.99,
|
100 |
+
"gae_lambda": 0.9,
|
101 |
+
"ent_coef": 0.0,
|
102 |
+
"vf_coef": 0.4,
|
103 |
+
"max_grad_norm": 0.5,
|
104 |
+
"normalize_advantage": false
|
105 |
+
}
|
a2c-HalfCheetahBulletEnv-v0/policy.optimizer.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:881db562d557671f8ffab3f407b366985fab53b319ab8a86670c9fe51101be5e
|
3 |
+
size 54142
|
a2c-HalfCheetahBulletEnv-v0/policy.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:81a732e964155b759d816eb58cf0534ed628c9f523ddcf17c76c11aa24012bb1
|
3 |
+
size 54718
|
a2c-HalfCheetahBulletEnv-v0/pytorch_variables.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:d030ad8db708280fcae77d87e973102039acd23a11bdecc3db8eb6c0ac940ee1
|
3 |
+
size 431
|
a2c-HalfCheetahBulletEnv-v0/system_info.txt
ADDED
@@ -0,0 +1,7 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
OS: Linux-5.11.0-38-generic-x86_64-with-glibc2.31 #42~20.04.1-Ubuntu SMP Tue Sep 28 20:41:07 UTC 2021
|
2 |
+
Python: 3.9.12
|
3 |
+
Stable-Baselines3: 1.5.0
|
4 |
+
PyTorch: 1.11.0+cu102
|
5 |
+
GPU Enabled: True
|
6 |
+
Numpy: 1.22.3
|
7 |
+
Gym: 0.21.0
|
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 0x7f29c7aff3a0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f29c7aff430>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f29c7aff4c0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f29c7aff550>", "_build": "<function ActorCriticPolicy._build at 0x7f29c7aff5e0>", "forward": "<function ActorCriticPolicy.forward at 0x7f29c7aff670>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f29c7aff700>", "_predict": "<function ActorCriticPolicy._predict at 0x7f29c7aff790>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f29c7aff820>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f29c7aff8b0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f29c7aff940>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f29c7cc8e00>"}, "verbose": 1, "policy_kwargs": {":type:": "<class 'dict'>", ":serialized:": "gAWVowAAAAAAAAB9lCiMDGxvZ19zdGRfaW5pdJRK/v///4wKb3J0aG9faW5pdJSJjA9vcHRpbWl6ZXJfY2xhc3OUjBN0b3JjaC5vcHRpbS5ybXNwcm9wlIwHUk1TcHJvcJSTlIwQb3B0aW1pemVyX2t3YXJnc5R9lCiMBWFscGhhlEc/764UeuFHrowDZXBzlEc+5Pi1iONo8YwMd2VpZ2h0X2RlY2F5lEsAdXUu", "log_std_init": -2, "ortho_init": false, "optimizer_class": "<class 'torch.optim.rmsprop.RMSprop'>", "optimizer_kwargs": {"alpha": 0.99, "eps": 1e-05, "weight_decay": 0}}, "observation_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "_shape": [26], "low": "[-inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf\n -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf]", "high": "[inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf\n inf inf inf inf inf inf inf inf]", "bounded_below": "[False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False]", "bounded_above": "[False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False]", "_np_random": null}, "action_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "_shape": [6], "low": "[-1. -1. -1. -1. -1. -1.]", "high": "[1. 1. 1. 1. 1. 1.]", "bounded_below": "[ True True True True True True]", "bounded_above": "[ True True True True True True]", "_np_random": null}, "n_envs": 8, "num_timesteps": 0, "_total_timesteps": 2000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1659352750.6474247, "learning_rate": 0.00096, "tensorboard_log": "./tensorboard", "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:": "gAWVewAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYIAAAAAAAAAAEBAQEBAQEBlIwFbnVtcHmUjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksIhZSMAUOUdJRSlC4="}, "_last_original_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVtQMAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJZAAwAAAAAAAAAAAAAAAAAAAACAPwAAAAAAAAAAAAAAAAAAAAAAAACA+WvUvgAAAAAaeeq9AAAAAKt0374AAAAA1tOePgAAAADcfAM+AAAAAIxHnD8AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAIA/AAAAAAAAAAAAAAAAAAAAAAAAAIBZg3e+AAAAAH0Crz0AAAAAVxPyvgAAAACtw54+AAAAADnaGr0AAAAAnJWTPwAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAgD8AAAAAAAAAAAAAAAAAAAAAAAAAgD5NoL4AAAAASHXUPQAAAAC1HF++AAAAAF/kgz4AAAAAQnGaPQAAAADJGJY/AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACAPwAAAAAAAAAAAAAAAAAAAAAAAACAcTXBvgAAAAARl4U9AAAAAPSztL4AAAAA5g5nPgAAAAAaJas9AAAAACEClz8AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAIA/AAAAAAAAAAAAAAAAAAAAAAAAAID/zee+AAAAADC98T0AAAAAYBHSvgAAAACh7mU+AAAAAP67ETsAAAAAqO6SPwAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAgD8AAAAAAAAAAAAAAAAAAAAAAAAAgISwz74AAAAAZZe9vAAAAAC/I/G+AAAAAO8lpj4AAAAAT03wPQAAAAAIdZU/AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACAPwAAAAAAAAAAAAAAAAAAAAAAAACA20DlvgAAAAAT4fY8AAAAANGWj74AAAAAnGKDPgAAAADw4xE9AAAAAFURnz8AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAIA/AAAAAAAAAAAAAAAAAAAAAAAAAIA7g9K+AAAAANvF2r0AAAAAAYG4vgAAAACr9ao+AAAAAMQp2D0AAAAAidKXPwAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJmNJSJiIeUUpQoSwOMATyUTk5OSv////9K/////0sAdJRiSwhLGoaUjAFDlHSUUpQu"}, "_episode_num": 0, "use_sde": true, "sde_sample_freq": -1, "_current_progress_remaining": 0.0, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 156250, "n_steps": 8, "gamma": 0.99, "gae_lambda": 0.9, "ent_coef": 0.0, "vf_coef": 0.4, "max_grad_norm": 0.5, "normalize_advantage": false, "system_info": {"OS": "Linux-5.11.0-38-generic-x86_64-with-glibc2.31 #42~20.04.1-Ubuntu SMP Tue Sep 28 20:41:07 UTC 2021", "Python": "3.9.12", "Stable-Baselines3": "1.5.0", "PyTorch": "1.11.0+cu102", "GPU Enabled": "True", "Numpy": "1.22.3", "Gym": "0.21.0"}}
|
replay.mp4
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:2039d93a92960e1736026fd44316515c265b3a380dd66a279e3e3d3f578068e9
|
3 |
+
size 1213533
|
results.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"mean_reward": 1498.700125034753, "std_reward": 811.270000971616, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-08-01T13:19:53.773557"}
|