Vishal-Padia
commited on
Commit
•
7364df9
1
Parent(s):
d8f8476
uploaded trained PPO 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 +99 -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 +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: 249.08 +/- 15.51
|
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 0x7d59c8a141f0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7d59c8a14280>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7d59c8a14310>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7d59c8a143a0>", "_build": "<function ActorCriticPolicy._build at 0x7d59c8a14430>", "forward": "<function ActorCriticPolicy.forward at 0x7d59c8a144c0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7d59c8a14550>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7d59c8a145e0>", "_predict": "<function ActorCriticPolicy._predict at 0x7d59c8a14670>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7d59c8a14700>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7d59c8a14790>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7d59c8a14820>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7d596a73f200>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000.0, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1732868073813288037, "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.zip
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:d483fbe81de3f30e0864c4d8e2bcf1eb4a7af5dfeea9811f669b7549fa153793
|
3 |
+
size 147511
|
ppo-LunarLander-v2/_stable_baselines3_version
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
2.0.0a5
|
ppo-LunarLander-v2/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 0x7d59c8a141f0>",
|
8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7d59c8a14280>",
|
9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7d59c8a14310>",
|
10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7d59c8a143a0>",
|
11 |
+
"_build": "<function ActorCriticPolicy._build at 0x7d59c8a14430>",
|
12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x7d59c8a144c0>",
|
13 |
+
"extract_features": "<function ActorCriticPolicy.extract_features at 0x7d59c8a14550>",
|
14 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7d59c8a145e0>",
|
15 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x7d59c8a14670>",
|
16 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7d59c8a14700>",
|
17 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7d59c8a14790>",
|
18 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7d59c8a14820>",
|
19 |
+
"__abstractmethods__": "frozenset()",
|
20 |
+
"_abc_impl": "<_abc._abc_data object at 0x7d596a73f200>"
|
21 |
+
},
|
22 |
+
"verbose": 1,
|
23 |
+
"policy_kwargs": {},
|
24 |
+
"num_timesteps": 1015808,
|
25 |
+
"_total_timesteps": 1000000.0,
|
26 |
+
"_num_timesteps_at_start": 0,
|
27 |
+
"seed": null,
|
28 |
+
"action_noise": null,
|
29 |
+
"start_time": 1732868073813288037,
|
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:": "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"
|
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/policy.optimizer.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:2e9d0a054c7005bb0fbf218d6ee0d7fc3c70bd919747667a33ec0a2ce3f2601d
|
3 |
+
size 87978
|
ppo-LunarLander-v2/policy.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:6dfec2faad254acaf3cccf17014e7469561cc02983392030ed535683e84fda6b
|
3 |
+
size 43634
|
ppo-LunarLander-v2/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/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 (200 kB). View file
|
|
results.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"mean_reward": 249.08191619999997, "std_reward": 15.514083988884046, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-11-29T08:44:40.686800"}
|