Adding first PPO optimized lander for LunarLander-v2
Browse files- .gitattributes +1 -0
- README.md +1 -1
- config.json +1 -1
- ppo-LunarLander-v2.zip +2 -2
- ppo-LunarLander-v2/data +29 -29
- ppo-LunarLander-v2/policy.optimizer.pth +1 -1
- ppo-LunarLander-v2/policy.pth +1 -1
- ppo-LunarLander-v2/system_info.txt +5 -5
- replay.mp4 +0 -0
- results.json +1 -1
.gitattributes
CHANGED
|
@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
|
|
| 33 |
*.zip filter=lfs diff=lfs merge=lfs -text
|
| 34 |
*.zst filter=lfs diff=lfs merge=lfs -text
|
| 35 |
*tfevents* filter=lfs diff=lfs merge=lfs -text
|
|
|
|
|
|
| 33 |
*.zip filter=lfs diff=lfs merge=lfs -text
|
| 34 |
*.zst filter=lfs diff=lfs merge=lfs -text
|
| 35 |
*tfevents* filter=lfs diff=lfs merge=lfs -text
|
| 36 |
+
replay.mp4 filter=lfs diff=lfs merge=lfs -text
|
README.md
CHANGED
|
@@ -16,7 +16,7 @@ model-index:
|
|
| 16 |
type: LunarLander-v2
|
| 17 |
metrics:
|
| 18 |
- type: mean_reward
|
| 19 |
-
value:
|
| 20 |
name: mean_reward
|
| 21 |
verified: false
|
| 22 |
---
|
|
|
|
| 16 |
type: LunarLander-v2
|
| 17 |
metrics:
|
| 18 |
- type: mean_reward
|
| 19 |
+
value: 273.35 +/- 12.45
|
| 20 |
name: mean_reward
|
| 21 |
verified: false
|
| 22 |
---
|
config.json
CHANGED
|
@@ -1 +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 0x7b3d91c25900>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7b3d91c25990>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7b3d91c25a20>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7b3d91c25ab0>", "_build": "<function ActorCriticPolicy._build at 0x7b3d91c25b40>", "forward": "<function ActorCriticPolicy.forward at 0x7b3d91c25bd0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7b3d91c25c60>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7b3d91c25cf0>", "_predict": "<function ActorCriticPolicy._predict at 0x7b3d91c25d80>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7b3d91c25e10>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7b3d91c25ea0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7b3d91c25f30>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7b3d91bcf180>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 507904, "_total_timesteps": 500000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1712873945052978027, "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": 124, "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": 0.9995, "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-6.1.58+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sat Nov 18 15:31:17 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.2.1+cu121", "GPU Enabled": "True", "Numpy": "1.25.2", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}
|
|
|
|
| 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 0x7b2930dfc400>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7b2930dfc4a0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7b2930dfc540>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7b2930dfc5e0>", "_build": "<function ActorCriticPolicy._build at 0x7b2930dfc680>", "forward": "<function ActorCriticPolicy.forward at 0x7b2930dfc720>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7b2930dfc7c0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7b2930dfc860>", "_predict": "<function ActorCriticPolicy._predict at 0x7b2930dfc900>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7b2930dfc9a0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7b2930dfca40>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7b2930dfcae0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7b2932e57980>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1750872639260652231, "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:": "gAWVhAAAAAAAAACME251bXB5Ll9jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksQhZSMAUOUdJRSlC4="}, "_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": 310, "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:": "gAWV3AAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFm51bXB5Ll9jb3JlLm11bHRpYXJyYXmUjAZzY2FsYXKUk5SMBW51bXB5lIwFZHR5cGWUk5SMAmk4lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGJDCAQAAAAAAAAAlIaUUpSMBXN0YXJ0lGgIaA5DCAAAAAAAAAAAlIaUUpSMBl9zaGFwZZQpjAVkdHlwZZRoDowKX25wX3JhbmRvbZROdWIu", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "n_steps": 2048, "gamma": 0.99, "gae_lambda": 0.95, "ent_coef": 0.0, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 64, "n_epochs": 10, "clip_range": {":type:": "<class 'function'>", ":serialized:": "gAWV1gIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwiVAZcAiQFTAJROhZQpjAFflIWUjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjExL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lIwEZnVuY5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUS4RDCPiAANgPEogKlEMAlIwDdmFslIWUKXSUUpR9lCiMC19fcGFja2FnZV9flIwYc3RhYmxlX2Jhc2VsaW5lczMuY29tbW9ulIwIX19uYW1lX1+UjB5zdGFibGVfYmFzZWxpbmVzMy5jb21tb24udXRpbHOUjAhfX2ZpbGVfX5SMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTEvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUdU5OaACMEF9tYWtlX2VtcHR5X2NlbGyUk5QpUpSFlHSUUpRoAIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaCF9lH2UKGgYjARmdW5jlIwMX19xdWFsbmFtZV9flIwZY29uc3RhbnRfZm4uPGxvY2Fscz4uZnVuY5SMD19fYW5ub3RhdGlvbnNfX5R9lIwOX19rd2RlZmF1bHRzX1+UTowMX19kZWZhdWx0c19flE6MCl9fbW9kdWxlX1+UaBmMB19fZG9jX1+UTowLX19jbG9zdXJlX1+UaACMCl9tYWtlX2NlbGyUk5RHP8mZmZmZmZqFlFKUhZSMF19jbG91ZHBpY2tsZV9zdWJtb2R1bGVzlF2UjAtfX2dsb2JhbHNfX5R9lHWGlIZSMC4="}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "system_info": {"OS": "Linux-6.1.123+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sun Mar 30 16:01:29 UTC 2025", "Python": "3.11.13", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.6.0+cu124", "GPU Enabled": "True", "Numpy": "2.0.2", "Cloudpickle": "3.1.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}
|
ppo-LunarLander-v2.zip
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
-
size
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:90760bc1949d9f2242f6db454fad2a220f575afd9b9afe647391967a3d048887
|
| 3 |
+
size 148039
|
ppo-LunarLander-v2/data
CHANGED
|
@@ -4,38 +4,38 @@
|
|
| 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
|
| 8 |
-
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at
|
| 9 |
-
"reset_noise": "<function ActorCriticPolicy.reset_noise at
|
| 10 |
-
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at
|
| 11 |
-
"_build": "<function ActorCriticPolicy._build at
|
| 12 |
-
"forward": "<function ActorCriticPolicy.forward at
|
| 13 |
-
"extract_features": "<function ActorCriticPolicy.extract_features at
|
| 14 |
-
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at
|
| 15 |
-
"_predict": "<function ActorCriticPolicy._predict at
|
| 16 |
-
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at
|
| 17 |
-
"get_distribution": "<function ActorCriticPolicy.get_distribution at
|
| 18 |
-
"predict_values": "<function ActorCriticPolicy.predict_values at
|
| 19 |
"__abstractmethods__": "frozenset()",
|
| 20 |
-
"_abc_impl": "<_abc._abc_data object at
|
| 21 |
},
|
| 22 |
"verbose": 1,
|
| 23 |
"policy_kwargs": {},
|
| 24 |
-
"num_timesteps":
|
| 25 |
-
"_total_timesteps":
|
| 26 |
"_num_timesteps_at_start": 0,
|
| 27 |
"seed": null,
|
| 28 |
"action_noise": null,
|
| 29 |
-
"start_time":
|
| 30 |
"learning_rate": 0.0003,
|
| 31 |
"tensorboard_log": null,
|
| 32 |
"_last_obs": {
|
| 33 |
":type:": "<class 'numpy.ndarray'>",
|
| 34 |
-
":serialized:": "
|
| 35 |
},
|
| 36 |
"_last_episode_starts": {
|
| 37 |
":type:": "<class 'numpy.ndarray'>",
|
| 38 |
-
":serialized:": "
|
| 39 |
},
|
| 40 |
"_last_original_obs": null,
|
| 41 |
"_episode_num": 0,
|
|
@@ -45,16 +45,16 @@
|
|
| 45 |
"_stats_window_size": 100,
|
| 46 |
"ep_info_buffer": {
|
| 47 |
":type:": "<class 'collections.deque'>",
|
| 48 |
-
":serialized:": "
|
| 49 |
},
|
| 50 |
"ep_success_buffer": {
|
| 51 |
":type:": "<class 'collections.deque'>",
|
| 52 |
":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
|
| 53 |
},
|
| 54 |
-
"_n_updates":
|
| 55 |
"observation_space": {
|
| 56 |
":type:": "<class 'gymnasium.spaces.box.Box'>",
|
| 57 |
-
":serialized:": "
|
| 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]",
|
|
@@ -69,7 +69,7 @@
|
|
| 69 |
},
|
| 70 |
"action_space": {
|
| 71 |
":type:": "<class 'gymnasium.spaces.discrete.Discrete'>",
|
| 72 |
-
":serialized:": "
|
| 73 |
"n": "4",
|
| 74 |
"start": "0",
|
| 75 |
"_shape": [],
|
|
@@ -77,23 +77,23 @@
|
|
| 77 |
"_np_random": null
|
| 78 |
},
|
| 79 |
"n_envs": 16,
|
| 80 |
-
"n_steps":
|
| 81 |
-
"gamma": 0.
|
| 82 |
-
"gae_lambda": 0.
|
| 83 |
-
"ent_coef": 0.
|
| 84 |
"vf_coef": 0.5,
|
| 85 |
"max_grad_norm": 0.5,
|
| 86 |
"batch_size": 64,
|
| 87 |
-
"n_epochs":
|
| 88 |
"clip_range": {
|
| 89 |
":type:": "<class 'function'>",
|
| 90 |
-
":serialized:": "
|
| 91 |
},
|
| 92 |
"clip_range_vf": null,
|
| 93 |
"normalize_advantage": true,
|
| 94 |
"target_kl": null,
|
| 95 |
"lr_schedule": {
|
| 96 |
":type:": "<class 'function'>",
|
| 97 |
-
":serialized:": "
|
| 98 |
}
|
| 99 |
}
|
|
|
|
| 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 0x7b2930dfc400>",
|
| 8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7b2930dfc4a0>",
|
| 9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7b2930dfc540>",
|
| 10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7b2930dfc5e0>",
|
| 11 |
+
"_build": "<function ActorCriticPolicy._build at 0x7b2930dfc680>",
|
| 12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x7b2930dfc720>",
|
| 13 |
+
"extract_features": "<function ActorCriticPolicy.extract_features at 0x7b2930dfc7c0>",
|
| 14 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7b2930dfc860>",
|
| 15 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x7b2930dfc900>",
|
| 16 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7b2930dfc9a0>",
|
| 17 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7b2930dfca40>",
|
| 18 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7b2930dfcae0>",
|
| 19 |
"__abstractmethods__": "frozenset()",
|
| 20 |
+
"_abc_impl": "<_abc._abc_data object at 0x7b2932e57980>"
|
| 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": 1750872639260652231,
|
| 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:": "gAWVhAAAAAAAAACME251bXB5Ll9jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksQhZSMAUOUdJRSlC4="
|
| 39 |
},
|
| 40 |
"_last_original_obs": null,
|
| 41 |
"_episode_num": 0,
|
|
|
|
| 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": 310,
|
| 55 |
"observation_space": {
|
| 56 |
":type:": "<class 'gymnasium.spaces.box.Box'>",
|
| 57 |
+
":serialized:": "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",
|
| 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]",
|
|
|
|
| 69 |
},
|
| 70 |
"action_space": {
|
| 71 |
":type:": "<class 'gymnasium.spaces.discrete.Discrete'>",
|
| 72 |
+
":serialized:": "gAWV3AAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFm51bXB5Ll9jb3JlLm11bHRpYXJyYXmUjAZzY2FsYXKUk5SMBW51bXB5lIwFZHR5cGWUk5SMAmk4lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGJDCAQAAAAAAAAAlIaUUpSMBXN0YXJ0lGgIaA5DCAAAAAAAAAAAlIaUUpSMBl9zaGFwZZQpjAVkdHlwZZRoDowKX25wX3JhbmRvbZROdWIu",
|
| 73 |
"n": "4",
|
| 74 |
"start": "0",
|
| 75 |
"_shape": [],
|
|
|
|
| 77 |
"_np_random": null
|
| 78 |
},
|
| 79 |
"n_envs": 16,
|
| 80 |
+
"n_steps": 2048,
|
| 81 |
+
"gamma": 0.99,
|
| 82 |
+
"gae_lambda": 0.95,
|
| 83 |
+
"ent_coef": 0.0,
|
| 84 |
"vf_coef": 0.5,
|
| 85 |
"max_grad_norm": 0.5,
|
| 86 |
"batch_size": 64,
|
| 87 |
+
"n_epochs": 10,
|
| 88 |
"clip_range": {
|
| 89 |
":type:": "<class 'function'>",
|
| 90 |
+
":serialized:": "gAWV1gIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwiVAZcAiQFTAJROhZQpjAFflIWUjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjExL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lIwEZnVuY5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUS4RDCPiAANgPEogKlEMAlIwDdmFslIWUKXSUUpR9lCiMC19fcGFja2FnZV9flIwYc3RhYmxlX2Jhc2VsaW5lczMuY29tbW9ulIwIX19uYW1lX1+UjB5zdGFibGVfYmFzZWxpbmVzMy5jb21tb24udXRpbHOUjAhfX2ZpbGVfX5SMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTEvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUdU5OaACMEF9tYWtlX2VtcHR5X2NlbGyUk5QpUpSFlHSUUpRoAIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaCF9lH2UKGgYjARmdW5jlIwMX19xdWFsbmFtZV9flIwZY29uc3RhbnRfZm4uPGxvY2Fscz4uZnVuY5SMD19fYW5ub3RhdGlvbnNfX5R9lIwOX19rd2RlZmF1bHRzX1+UTowMX19kZWZhdWx0c19flE6MCl9fbW9kdWxlX1+UaBmMB19fZG9jX1+UTowLX19jbG9zdXJlX1+UaACMCl9tYWtlX2NlbGyUk5RHP8mZmZmZmZqFlFKUhZSMF19jbG91ZHBpY2tsZV9zdWJtb2R1bGVzlF2UjAtfX2dsb2JhbHNfX5R9lHWGlIZSMC4="
|
| 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
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 88362
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:e6bae7cd1a7396054f2e61a8d9352ea8a7ec312d068ac4aabb7e34f041d5f68a
|
| 3 |
size 88362
|
ppo-LunarLander-v2/policy.pth
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 43762
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:28df1fab5178dfc2a63b19043dc325ea6e99d6c366e26de94c5d30cf98ad48d7
|
| 3 |
size 43762
|
ppo-LunarLander-v2/system_info.txt
CHANGED
|
@@ -1,9 +1,9 @@
|
|
| 1 |
-
- OS: Linux-6.1.
|
| 2 |
-
- Python: 3.
|
| 3 |
- Stable-Baselines3: 2.0.0a5
|
| 4 |
-
- PyTorch: 2.
|
| 5 |
- GPU Enabled: True
|
| 6 |
-
- Numpy:
|
| 7 |
-
- Cloudpickle:
|
| 8 |
- Gymnasium: 0.28.1
|
| 9 |
- OpenAI Gym: 0.25.2
|
|
|
|
| 1 |
+
- OS: Linux-6.1.123+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sun Mar 30 16:01:29 UTC 2025
|
| 2 |
+
- Python: 3.11.13
|
| 3 |
- Stable-Baselines3: 2.0.0a5
|
| 4 |
+
- PyTorch: 2.6.0+cu124
|
| 5 |
- GPU Enabled: True
|
| 6 |
+
- Numpy: 2.0.2
|
| 7 |
+
- Cloudpickle: 3.1.1
|
| 8 |
- Gymnasium: 0.28.1
|
| 9 |
- OpenAI Gym: 0.25.2
|
replay.mp4
CHANGED
|
Binary files a/replay.mp4 and b/replay.mp4 differ
|
|
|
results.json
CHANGED
|
@@ -1 +1 @@
|
|
| 1 |
-
{"mean_reward":
|
|
|
|
| 1 |
+
{"mean_reward": 273.35101000000003, "std_reward": 12.450747671996302, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2025-06-25T18:05:18.222322"}
|