spadaal commited on
Commit
6479400
1 Parent(s): 1a73a90

Upload PPO LunarLander-v2 model

Browse files
README.md CHANGED
@@ -16,7 +16,7 @@ model-index:
16
  type: LunarLander-v2
17
  metrics:
18
  - type: mean_reward
19
- value: 216.68 +/- 88.68
20
  name: mean_reward
21
  verified: false
22
  ---
 
16
  type: LunarLander-v2
17
  metrics:
18
  - type: mean_reward
19
+ value: 265.19 +/- 28.27
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 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 0x7f3c6b055790>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f3c6b055820>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f3c6b0558b0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f3c6b055940>", "_build": "<function ActorCriticPolicy._build at 0x7f3c6b0559d0>", "forward": "<function ActorCriticPolicy.forward at 0x7f3c6b055a60>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f3c6b055af0>", "_predict": "<function ActorCriticPolicy._predict at 0x7f3c6b055b80>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f3c6b055c10>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f3c6b055ca0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f3c6b055d30>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f3c6b04cf30>"}, "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": 1, "num_timesteps": 1000448, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1670930030749297135, "learning_rate": 0.0003, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": null, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdAAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYBAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwGFlIwBQ5R0lFKULg=="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.00044800000000000395, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 4332, "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:": "gAWVwwIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSC91c3IvbG9jYWwvbGliL3B5dGhvbjMuOC9kaXN0LXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZSMBGZ1bmOUS4BDAgABlIwDdmFslIWUKXSUUpR9lCiMC19fcGFja2FnZV9flIwYc3RhYmxlX2Jhc2VsaW5lczMuY29tbW9ulIwIX19uYW1lX1+UjB5zdGFibGVfYmFzZWxpbmVzMy5jb21tb24udXRpbHOUjAhfX2ZpbGVfX5SMSC91c3IvbG9jYWwvbGliL3B5dGhvbjMuOC9kaXN0LXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZR1Tk5oAIwQX21ha2VfZW1wdHlfY2VsbJSTlClSlIWUdJRSlIwcY2xvdWRwaWNrbGUuY2xvdWRwaWNrbGVfZmFzdJSMEl9mdW5jdGlvbl9zZXRzdGF0ZZSTlGgffZR9lChoFmgNjAxfX3F1YWxuYW1lX1+UjBljb25zdGFudF9mbi48bG9jYWxzPi5mdW5jlIwPX19hbm5vdGF0aW9uc19flH2UjA5fX2t3ZGVmYXVsdHNfX5ROjAxfX2RlZmF1bHRzX1+UTowKX19tb2R1bGVfX5RoF4wHX19kb2NfX5ROjAtfX2Nsb3N1cmVfX5RoAIwKX21ha2VfY2VsbJSTlEc/yZmZmZmZmoWUUpSFlIwXX2Nsb3VkcGlja2xlX3N1Ym1vZHVsZXOUXZSMC19fZ2xvYmFsc19flH2UdYaUhlIwLg=="}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "system_info": {"OS": "Linux-5.10.133+-x86_64-with-glibc2.27 #1 SMP Fri Aug 26 08:44:51 UTC 2022", "Python": "3.8.16", "Stable-Baselines3": "1.6.2", "PyTorch": "1.13.0+cu116", "GPU Enabled": "True", "Numpy": "1.21.6", "Gym": "0.21.0"}}
 
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 0x7ff8851d7e50>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7ff8851d7ee0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7ff8851d7f70>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7ff8851de040>", "_build": "<function ActorCriticPolicy._build at 0x7ff8851de0d0>", "forward": "<function ActorCriticPolicy.forward at 0x7ff8851de160>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7ff8851de1f0>", "_predict": "<function ActorCriticPolicy._predict at 0x7ff8851de280>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7ff8851de310>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7ff8851de3a0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7ff8851de430>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7ff8851d9330>"}, "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": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1671721992456136260, "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:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAABAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////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": 248, "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-5.10.133+-x86_64-with-glibc2.27 #1 SMP Fri Aug 26 08:44:51 UTC 2022", "Python": "3.8.16", "Stable-Baselines3": "1.6.2", "PyTorch": "1.13.0+cu116", "GPU Enabled": "True", "Numpy": "1.21.6", "Gym": "0.21.0"}}
ppo-LunarLander-v2.zip CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:c30f8b609e16033f634c40d3dc246cb9d49bc75f91de5d6ea16e704018d1a2ce
3
- size 146337
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:5f32936c31f319af12beb74fae7122f24985649eb850fdf28d0de73dec9e0210
3
+ size 147170
ppo-LunarLander-v2/data CHANGED
@@ -4,19 +4,19 @@
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 0x7f3c6b055790>",
8
- "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f3c6b055820>",
9
- "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f3c6b0558b0>",
10
- "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f3c6b055940>",
11
- "_build": "<function ActorCriticPolicy._build at 0x7f3c6b0559d0>",
12
- "forward": "<function ActorCriticPolicy.forward at 0x7f3c6b055a60>",
13
- "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f3c6b055af0>",
14
- "_predict": "<function ActorCriticPolicy._predict at 0x7f3c6b055b80>",
15
- "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f3c6b055c10>",
16
- "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f3c6b055ca0>",
17
- "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f3c6b055d30>",
18
  "__abstractmethods__": "frozenset()",
19
- "_abc_impl": "<_abc_data object at 0x7f3c6b04cf30>"
20
  },
21
  "verbose": 1,
22
  "policy_kwargs": {},
@@ -41,38 +41,41 @@
41
  "dtype": "int64",
42
  "_np_random": null
43
  },
44
- "n_envs": 1,
45
- "num_timesteps": 1000448,
46
  "_total_timesteps": 1000000,
47
  "_num_timesteps_at_start": 0,
48
  "seed": null,
49
  "action_noise": null,
50
- "start_time": 1670930030749297135,
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": null,
 
 
 
58
  "_last_episode_starts": {
59
  ":type:": "<class 'numpy.ndarray'>",
60
- ":serialized:": "gAWVdAAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYBAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwGFlIwBQ5R0lFKULg=="
61
  },
62
  "_last_original_obs": null,
63
  "_episode_num": 0,
64
  "use_sde": false,
65
  "sde_sample_freq": -1,
66
- "_current_progress_remaining": -0.00044800000000000395,
67
  "ep_info_buffer": {
68
  ":type:": "<class 'collections.deque'>",
69
- ":serialized:": "gAWVUxAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIGAgCZKhtcECUhpRSlIwBbJRNKwGMAXSUR0Ce1qFVT72tdX2UKGgGaAloD0MISfYINYOKcECUhpRSlGgVTSMBaBZHQJ7YXsw+MZR1fZQoaAZoCWgPQwhENLqDGBBwQJSGlFKUaBVNAgFoFkdAntoQ1R+BpnV9lChoBmgJaA9DCESlETN7jm9AlIaUUpRoFU0KAWgWR0Ce27W43FUAdX2UKGgGaAloD0MIvHX+7bKZQ0CUhpRSlGgVS7loFkdAntzLs8gZCXV9lChoBmgJaA9DCE93nngOuXFAlIaUUpRoFU0iAWgWR0Ce39G6wt8NdX2UKGgGaAloD0MIKv7viEpwcECUhpRSlGgVTRcBaBZHQJ7hZIFvAGl1fZQoaAZoCWgPQwjwi0tV2mZHQJSGlFKUaBVL0GgWR0Ce4pI3R5TqdX2UKGgGaAloD0MI2CrB4rB3cUCUhpRSlGgVTQwBaBZHQJ7lWR2bG3p1fZQoaAZoCWgPQwivQPSkTJI8QJSGlFKUaBVLymgWR0Ce5oi48U22dX2UKGgGaAloD0MIbAVNS6xOQECUhpRSlGgVS+RoFkdAnufVS0jTrnV9lChoBmgJaA9DCLRyLzAriEpAlIaUUpRoFUuZaBZHQJ7ovo/zJ6p1fZQoaAZoCWgPQwioqWVrfcdMQJSGlFKUaBVLp2gWR0Ce6aG0eEIxdX2UKGgGaAloD0MI/rRRnY59cECUhpRSlGgVTQwBaBZHQJ7rJUipvP11fZQoaAZoCWgPQwiXjc75KU5EQJSGlFKUaBVL3WgWR0Ce7aWJ79hrdX2UKGgGaAloD0MI96+sNGlHcUCUhpRSlGgVTQoBaBZHQJ7vMHzH0bt1fZQoaAZoCWgPQwg0go3r351MQJSGlFKUaBVLwWgWR0Ce8ESJTER8dX2UKGgGaAloD0MI86rOagFlcECUhpRSlGgVTSABaBZHQJ7yBg0CRwJ1fZQoaAZoCWgPQwi37BD/MERxQJSGlFKUaBVNLAFoFkdAnvUimVJL/XV9lChoBmgJaA9DCDhorz4ecktAlIaUUpRoFUvCaBZHQJ72NPDYRNB1fZQoaAZoCWgPQwgBGM+goTtxQJSGlFKUaBVL8mgWR0Ce94nhbW3CdX2UKGgGaAloD0MIxqUqbXHlcECUhpRSlGgVTTIBaBZHQJ75fyAhB7h1fZQoaAZoCWgPQwgNqg1OxKJxQJSGlFKUaBVNHAFoFkdAnvx5aaCtinV9lChoBmgJaA9DCHxCdt7G0VBAlIaUUpRoFUvHaBZHQJ79vo5ggHN1fZQoaAZoCWgPQwjHEtbG2OVwQJSGlFKUaBVNFAFoFkdAnv90zXSSeXV9lChoBmgJaA9DCF5ortOIW3BAlIaUUpRoFU0zAWgWR0CfAqUHpr1vdX2UKGgGaAloD0MItwvNdRo9M0CUhpRSlGgVS8ZoFkdAnwPJ8neBQXV9lChoBmgJaA9DCFfrxOV46UxAlIaUUpRoFUvHaBZHQJ8FGrKeTV51fZQoaAZoCWgPQwglyt5SzoJrQJSGlFKUaBVNJAFoFkdAnwbnXyy2QXV9lChoBmgJaA9DCK8JaY1BfUVAlIaUUpRoFUvsaBZHQJ8IJbkfcN91fZQoaAZoCWgPQwhfRrHcUlBxQJSGlFKUaBVNCQFoFkdAnwsMtTUAk3V9lChoBmgJaA9DCOKQDaRLIHFAlIaUUpRoFUv2aBZHQJ8NCcawUxp1fZQoaAZoCWgPQwiQuwhTFI9wQJSGlFKUaBVNEQFoFkdAnw6o82aUinV9lChoBmgJaA9DCE2iXvBpA3FAlIaUUpRoFU0CAWgWR0CfEEDB/I8ydX2UKGgGaAloD0MIKo9uhEVFNUCUhpRSlGgVS9VoFkdAnxK0+1SflXV9lChoBmgJaA9DCAO0rWad63FAlIaUUpRoFU0XAWgWR0CfFGFajesQdX2UKGgGaAloD0MIOzdtxmlEQECUhpRSlGgVS+FoFkdAnxWhXCCSR3V9lChoBmgJaA9DCEaVYdxNnHFAlIaUUpRoFU0AAWgWR0CfFyjjJdSmdX2UKGgGaAloD0MIbOnRVE9OS0CUhpRSlGgVS75oFkdAnxmBnJ1aGHV9lChoBmgJaA9DCOGYZU8COUlAlIaUUpRoFUvLaBZHQJ8aoUtZmqZ1fZQoaAZoCWgPQwhLj6Z6cq5xQJSGlFKUaBVL72gWR0CfG/9fkWAPdX2UKGgGaAloD0MItahPcodNcECUhpRSlGgVTR0BaBZHQJ8dpYISlFd1fZQoaAZoCWgPQwgTRx6I7ElyQJSGlFKUaBVL6WgWR0CfHw6ltTDPdX2UKGgGaAloD0MI078klalLb0CUhpRSlGgVS/NoFkdAnyHDaPCEYnV9lChoBmgJaA9DCLXEymgk8nJAlIaUUpRoFUvcaBZHQJ8jBFc6eXl1fZQoaAZoCWgPQwgE5bZ9j7FvQJSGlFKUaBVNJgFoFkdAnyTGcBltj3V9lChoBmgJaA9DCIEhq1u92XFAlIaUUpRoFU0PAWgWR0CfJ54uK4x2dX2UKGgGaAloD0MICiyAKYOqb0CUhpRSlGgVTQ0BaBZHQJ8pH38GcF11fZQoaAZoCWgPQwjxRXu8UAhxQJSGlFKUaBVNEwFoFkdAnyqxYzSCv3V9lChoBmgJaA9DCI5XIHpS6jRAlIaUUpRoFUvQaBZHQJ8r0mPYFq11fZQoaAZoCWgPQwhlprT+lj1sQJSGlFKUaBVNGgFoFkdAny6/KEFnqXV9lChoBmgJaA9DCH/3jhrTBXFAlIaUUpRoFUv+aBZHQJ8wLJIUahp1fZQoaAZoCWgPQwjIeJRKeCpxQJSGlFKUaBVNFAFoFkdAnzGtkJ8fFXV9lChoBmgJaA9DCE5hpYJKDnNAlIaUUpRoFU0JAWgWR0CfMyxb0OEvdX2UKGgGaAloD0MIFytqMA3UcUCUhpRSlGgVTQMBaBZHQJ819mYjSoh1fZQoaAZoCWgPQwjIRbWI6HdwQJSGlFKUaBVNFgFoFkdAnzeERaouPHV9lChoBmgJaA9DCJeMYyR7rlJAlIaUUpRoFUu0aBZHQJ84dRzijtZ1fZQoaAZoCWgPQwhYqgt42VFxQJSGlFKUaBVNAgFoFkdAnzn7W7OE/XV9lChoBmgJaA9DCJS9pZwviE1AlIaUUpRoFUvJaBZHQJ87Fhvze411fZQoaAZoCWgPQwhiuhCr/8ZwQJSGlFKUaBVNGgFoFkdAnz3sOLBKtnV9lChoBmgJaA9DCFVOe0oOHXFAlIaUUpRoFU0ZAWgWR0CfP5T4L1EmdX2UKGgGaAloD0MIea9amTAJcECUhpRSlGgVTR8BaBZHQJ9BUTufEn91fZQoaAZoCWgPQwhuh4bFKMBvQJSGlFKUaBVNHQFoFkdAn0RVJHy3C3V9lChoBmgJaA9DCOPfZ1w42kJAlIaUUpRoFUvVaBZHQJ9FeWa+evp1fZQoaAZoCWgPQwhi9x3DY6VvQJSGlFKUaBVNHwFoFkdAn0cka2nbZnV9lChoBmgJaA9DCCeIug8AunJAlIaUUpRoFU0FAWgWR0CfSJspXp4bdX2UKGgGaAloD0MIa4DSUKOkSUCUhpRSlGgVS8hoFkdAn0mtnTRYzXV9lChoBmgJaA9DCMh8QKAz+0tAlIaUUpRoFUuzaBZHQJ9L4nXumaZ1fZQoaAZoCWgPQwh9k6ZB0YRxQJSGlFKUaBVNBwFoFkdAn01jDjzZpXV9lChoBmgJaA9DCGyzsRLz5D5AlIaUUpRoFUvIaBZHQJ9OeH6/IsB1fZQoaAZoCWgPQwh64c6Fkf9uQJSGlFKUaBVNEAFoFkdAn0/z2i+L33V9lChoBmgJaA9DCNqM0xBVvkpAlIaUUpRoFUusaBZHQJ9SI0xdpqR1fZQoaAZoCWgPQwjTF0LOe55wQJSGlFKUaBVNFAFoFkdAn1PcZHd43XV9lChoBmgJaA9DCKshcY+ly0pAlIaUUpRoFUvSaBZHQJ9VF96Tnq51fZQoaAZoCWgPQwgDBkmfVo1wQJSGlFKUaBVNBwFoFkdAn1apHuqm0nV9lChoBmgJaA9DCCy2SUWjCnFAlIaUUpRoFUvwaBZHQJ9ZX5bhWHV1fZQoaAZoCWgPQwh1VaAWQ4xwQJSGlFKUaBVL32gWR0CfWqZTho/SdX2UKGgGaAloD0MIWRgip+9LcUCUhpRSlGgVS/5oFkdAn1wkCJXQt3V9lChoBmgJaA9DCCzVBbzM1DNAlIaUUpRoFUvJaBZHQJ9dP8YQ8Ol1fZQoaAZoCWgPQwhgOUIG8vdsQJSGlFKUaBVNCAFoFkdAn17Jhz/6wnV9lChoBmgJaA9DCLw/3qvWD3BAlIaUUpRoFUvyaBZHQJ9hb8XN1Qt1fZQoaAZoCWgPQwhycOmY85VtQJSGlFKUaBVNIQFoFkdAn2MXRCx/u3V9lChoBmgJaA9DCLX7VYDvn3BAlIaUUpRoFU0KAWgWR0CfZJTy8SPEdX2UKGgGaAloD0MIQxuADYgqbsCUhpRSlGgVS5poFkdAn2VhQvYe1nV9lChoBmgJaA9DCByVm6hlxnBAlIaUUpRoFU04AWgWR0CfaIJOWSlndX2UKGgGaAloD0MITWVR2MWnbUCUhpRSlGgVTRUBaBZHQJ9qJfYzzmR1fZQoaAZoCWgPQwiIKvwZXndxQJSGlFKUaBVNlwFoFkdAn2yHOSntOXV9lChoBmgJaA9DCMgJE0ZzlXFAlIaUUpRoFUvvaBZHQJ9vKc0+C9R1fZQoaAZoCWgPQwgBUTBjChxSQJSGlFKUaBVLwGgWR0CfcDj+717IdX2UKGgGaAloD0MIOrGH9jEFb0CUhpRSlGgVTRQBaBZHQJ9x37uUliV1fZQoaAZoCWgPQwhZUu4+x59FQJSGlFKUaBVLkGgWR0CfcqQyhzvJdX2UKGgGaAloD0MIA3gLJCiDcUCUhpRSlGgVTScBaBZHQJ90WgdwNsp1fZQoaAZoCWgPQwgVxEDXvhBvQJSGlFKUaBVNEAFoFkdAn3cxJmNBGHV9lChoBmgJaA9DCDuNtFTeSE5AlIaUUpRoFUu9aBZHQJ94OqaPS2J1fZQoaAZoCWgPQwhSDmYToGBwQJSGlFKUaBVNHQFoFkdAn3nfsZ5zHXV9lChoBmgJaA9DCDJ07KAS+m5AlIaUUpRoFU03AWgWR0Cfe60h/y5JdX2UKGgGaAloD0MIiSe7mdHVSUCUhpRSlGgVS8doFkdAn34RplBhQXV9lChoBmgJaA9DCGRam8b2QXFAlIaUUpRoFU0RAWgWR0Cff6vLowEhdX2UKGgGaAloD0MIf73CgvvxcUCUhpRSlGgVS/VoFkdAn4EW2sq8UXV9lChoBmgJaA9DCLddaK5Tj3FAlIaUUpRoFUv1aBZHQJ+CiakRBeJ1ZS4="
70
  },
71
  "ep_success_buffer": {
72
  ":type:": "<class 'collections.deque'>",
73
  ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
74
  },
75
- "_n_updates": 4332,
76
  "n_steps": 1024,
77
  "gamma": 0.999,
78
  "gae_lambda": 0.98,
 
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 0x7ff8851d7e50>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7ff8851d7ee0>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7ff8851d7f70>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7ff8851de040>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7ff8851de0d0>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7ff8851de160>",
13
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7ff8851de1f0>",
14
+ "_predict": "<function ActorCriticPolicy._predict at 0x7ff8851de280>",
15
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7ff8851de310>",
16
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7ff8851de3a0>",
17
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7ff8851de430>",
18
  "__abstractmethods__": "frozenset()",
19
+ "_abc_impl": "<_abc_data object at 0x7ff8851d9330>"
20
  },
21
  "verbose": 1,
22
  "policy_kwargs": {},
 
41
  "dtype": "int64",
42
  "_np_random": null
43
  },
44
+ "n_envs": 16,
45
+ "num_timesteps": 1015808,
46
  "_total_timesteps": 1000000,
47
  "_num_timesteps_at_start": 0,
48
  "seed": null,
49
  "action_noise": null,
50
+ "start_time": 1671721992456136260,
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:": "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"
60
+ },
61
  "_last_episode_starts": {
62
  ":type:": "<class 'numpy.ndarray'>",
63
+ ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAABAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////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:": "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"
73
  },
74
  "ep_success_buffer": {
75
  ":type:": "<class 'collections.deque'>",
76
  ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
77
  },
78
+ "_n_updates": 248,
79
  "n_steps": 1024,
80
  "gamma": 0.999,
81
  "gae_lambda": 0.98,
ppo-LunarLander-v2/policy.optimizer.pth CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:9bd0a6e85de4e3d13cb5a60e02d3bb78ecc4bf82fd850f6921071ea846aa93d0
3
- size 88057
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:c1a895c5ce6e0ba7617045d55f7a3a601cce1b90741960cee9579de014e90b3a
3
+ size 87929
ppo-LunarLander-v2/policy.pth CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:b4ecd278a78510306fe399161a1e6733bc14c2f26aba59bac6a7d031677b1d91
3
  size 43201
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:b3cd5b1b5e28aaa0c1f731980d4f0b18538747e9c157b518c1cf5240ac7dd91b
3
  size 43201
replay.mp4 CHANGED
Binary files a/replay.mp4 and b/replay.mp4 differ
 
results.json CHANGED
@@ -1 +1 @@
1
- {"mean_reward": 216.68229230243986, "std_reward": 88.67748164657236, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-12-13T12:27:00.378239"}
 
1
+ {"mean_reward": 265.1911167302251, "std_reward": 28.273382690571925, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-12-22T15:34:15.354699"}