PPO Agent, AJE_AGENT_2
Browse files- AJE_AGENT_2.zip +2 -2
- AJE_AGENT_2/data +22 -22
- AJE_AGENT_2/policy.optimizer.pth +2 -2
- AJE_AGENT_2/policy.pth +1 -1
- README.md +1 -1
- config.json +1 -1
- replay.mp4 +2 -2
- results.json +1 -1
AJE_AGENT_2.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:d9e7504c7b4a2307d93e22913519b84f6ac745c664e764575c90ffb14773b070
|
3 |
+
size 143425
|
AJE_AGENT_2/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
|
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 |
-
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at
|
14 |
-
"_predict": "<function ActorCriticPolicy._predict at
|
15 |
-
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at
|
16 |
-
"get_distribution": "<function ActorCriticPolicy.get_distribution at
|
17 |
-
"predict_values": "<function ActorCriticPolicy.predict_values at
|
18 |
"__abstractmethods__": "frozenset()",
|
19 |
-
"_abc_impl": "<_abc_data object at
|
20 |
},
|
21 |
"verbose": 1,
|
22 |
"policy_kwargs": {},
|
@@ -41,26 +41,26 @@
|
|
41 |
"dtype": "int64",
|
42 |
"_np_random": null
|
43 |
},
|
44 |
-
"n_envs":
|
45 |
"num_timesteps": 10002432,
|
46 |
"_total_timesteps": 10000000,
|
47 |
"_num_timesteps_at_start": 0,
|
48 |
"seed": null,
|
49 |
"action_noise": null,
|
50 |
-
"start_time":
|
51 |
-
"learning_rate": 0.
|
52 |
"tensorboard_log": null,
|
53 |
"lr_schedule": {
|
54 |
":type:": "<class 'function'>",
|
55 |
-
":serialized:": "gAWVvwIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwNX2J1aWx0aW5fdHlwZZSTlIwKTGFtYmRhVHlwZZSFlFKUKGgCjAhDb2RlVHlwZZSFlFKUKEsBSwBLAUsBSxNDBIgAUwCUToWUKYwBX5SFlIxIL3Vzci9sb2NhbC9saWIvcHl0aG9uMy43L2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lIwEZnVuY5RLgEMCAAGUjAN2YWyUhZQpdJRSlH2UKIwLX19wYWNrYWdlX1+UjBhzdGFibGVfYmFzZWxpbmVzMy5jb21tb26UjAhfX25hbWVfX5SMHnN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi51dGlsc5SMCF9fZmlsZV9flIxIL3Vzci9sb2NhbC9saWIvcHl0aG9uMy43L2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaCB9lH2UKGgXaA6MDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+
|
56 |
},
|
57 |
"_last_obs": {
|
58 |
":type:": "<class 'numpy.ndarray'>",
|
59 |
-
":serialized:": "
|
60 |
},
|
61 |
"_last_episode_starts": {
|
62 |
":type:": "<class 'numpy.ndarray'>",
|
63 |
-
":serialized:": "
|
64 |
},
|
65 |
"_last_original_obs": null,
|
66 |
"_episode_num": 0,
|
@@ -69,21 +69,21 @@
|
|
69 |
"_current_progress_remaining": -0.00024320000000011,
|
70 |
"ep_info_buffer": {
|
71 |
":type:": "<class 'collections.deque'>",
|
72 |
-
":serialized:": "
|
73 |
},
|
74 |
"ep_success_buffer": {
|
75 |
":type:": "<class 'collections.deque'>",
|
76 |
":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
|
77 |
},
|
78 |
-
"_n_updates":
|
79 |
"n_steps": 1024,
|
80 |
"gamma": 0.999,
|
81 |
"gae_lambda": 0.98,
|
82 |
"ent_coef": 0.01,
|
83 |
"vf_coef": 0.5,
|
84 |
"max_grad_norm": 0.5,
|
85 |
-
"batch_size":
|
86 |
-
"n_epochs":
|
87 |
"clip_range": {
|
88 |
":type:": "<class 'function'>",
|
89 |
":serialized:": "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"
|
|
|
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 0x7fdb73c0d290>",
|
8 |
+
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fdb73c0d320>",
|
9 |
+
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fdb73c0d3b0>",
|
10 |
+
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fdb73c0d440>",
|
11 |
+
"_build": "<function ActorCriticPolicy._build at 0x7fdb73c0d4d0>",
|
12 |
+
"forward": "<function ActorCriticPolicy.forward at 0x7fdb73c0d560>",
|
13 |
+
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fdb73c0d5f0>",
|
14 |
+
"_predict": "<function ActorCriticPolicy._predict at 0x7fdb73c0d680>",
|
15 |
+
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fdb73c0d710>",
|
16 |
+
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fdb73c0d7a0>",
|
17 |
+
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7fdb73c0d830>",
|
18 |
"__abstractmethods__": "frozenset()",
|
19 |
+
"_abc_impl": "<_abc_data object at 0x7fdb73be70c0>"
|
20 |
},
|
21 |
"verbose": 1,
|
22 |
"policy_kwargs": {},
|
|
|
41 |
"dtype": "int64",
|
42 |
"_np_random": null
|
43 |
},
|
44 |
+
"n_envs": 4,
|
45 |
"num_timesteps": 10002432,
|
46 |
"_total_timesteps": 10000000,
|
47 |
"_num_timesteps_at_start": 0,
|
48 |
"seed": null,
|
49 |
"action_noise": null,
|
50 |
+
"start_time": 1652359024.4056726,
|
51 |
+
"learning_rate": 0.003,
|
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:": "gAWV9QAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJaAAAAAAAAAALrifD7bbn0/6bKcPu16o75DdRM/wcSHPgAAAAAAAAAAZpMEvSOZDj3T64o+Tn4bvi8yhD0g5RY9AAAAAAAAAACtLQW+0fiuPT2wlT4aC1K+CVKdvOIm0jwAAAAAAAAAAGZ4gTyHu6o+I6NlvAt4pb5MRFe8kH4uvQAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksESwiGlIwBQ5R0lFKULg=="
|
60 |
},
|
61 |
"_last_episode_starts": {
|
62 |
":type:": "<class 'numpy.ndarray'>",
|
63 |
+
":serialized:": "gAWVdwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYEAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwSFlIwBQ5R0lFKULg=="
|
64 |
},
|
65 |
"_last_original_obs": null,
|
66 |
"_episode_num": 0,
|
|
|
69 |
"_current_progress_remaining": -0.00024320000000011,
|
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": 19536,
|
79 |
"n_steps": 1024,
|
80 |
"gamma": 0.999,
|
81 |
"gae_lambda": 0.98,
|
82 |
"ent_coef": 0.01,
|
83 |
"vf_coef": 0.5,
|
84 |
"max_grad_norm": 0.5,
|
85 |
+
"batch_size": 4096,
|
86 |
+
"n_epochs": 8,
|
87 |
"clip_range": {
|
88 |
":type:": "<class 'function'>",
|
89 |
":serialized:": "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"
|
AJE_AGENT_2/policy.optimizer.pth
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 sha256:0283de8f7897248076524f13aefb3d2975830a4627e74f61d439cbc551df3d14
|
3 |
+
size 84829
|
AJE_AGENT_2/policy.pth
CHANGED
@@ -1,3 +1,3 @@
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
-
oid sha256:
|
3 |
size 43201
|
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:8e41dfd310c4f0fccc36db05b80974b95cb181876108a47d3cea54774fe99db5
|
3 |
size 43201
|
README.md
CHANGED
@@ -10,7 +10,7 @@ model-index:
|
|
10 |
results:
|
11 |
- metrics:
|
12 |
- type: mean_reward
|
13 |
-
value:
|
14 |
name: mean_reward
|
15 |
task:
|
16 |
type: reinforcement-learning
|
|
|
10 |
results:
|
11 |
- metrics:
|
12 |
- type: mean_reward
|
13 |
+
value: 284.86 +/- 16.57
|
14 |
name: mean_reward
|
15 |
task:
|
16 |
type: reinforcement-learning
|
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 0x7f6c8241e320>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f6c8241e3b0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f6c8241e440>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f6c8241e4d0>", "_build": "<function ActorCriticPolicy._build at 0x7f6c8241e560>", "forward": "<function ActorCriticPolicy.forward at 0x7f6c8241e5f0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f6c8241e680>", "_predict": "<function ActorCriticPolicy._predict at 0x7f6c8241e710>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f6c8241e7a0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f6c8241e830>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f6c8241e8c0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f6c82465a50>"}, "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": 8, "num_timesteps": 10002432, "_total_timesteps": 10000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1652268870.216788, "learning_rate": 0.0003, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "gAWVvwIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwNX2J1aWx0aW5fdHlwZZSTlIwKTGFtYmRhVHlwZZSFlFKUKGgCjAhDb2RlVHlwZZSFlFKUKEsBSwBLAUsBSxNDBIgAUwCUToWUKYwBX5SFlIxIL3Vzci9sb2NhbC9saWIvcHl0aG9uMy43L2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lIwEZnVuY5RLgEMCAAGUjAN2YWyUhZQpdJRSlH2UKIwLX19wYWNrYWdlX1+UjBhzdGFibGVfYmFzZWxpbmVzMy5jb21tb26UjAhfX25hbWVfX5SMHnN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi51dGlsc5SMCF9fZmlsZV9flIxIL3Vzci9sb2NhbC9saWIvcHl0aG9uMy43L2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaCB9lH2UKGgXaA6MDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgYjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz8zqSowVTJhhZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"}, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "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"}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVewAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYIAAAAAAAAAAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksIhZSMAUOUdJRSlC4="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.00024320000000011, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 7326, "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": 512, "n_epochs": 6, "clip_range": {":type:": "<class 'function'>", ":serialized:": "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"}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "system_info": {"OS": "Linux-5.4.188+-x86_64-with-Ubuntu-18.04-bionic #1 SMP Sun Apr 24 10:03:06 PDT 2022", "Python": "3.7.13", "Stable-Baselines3": "1.5.0", "PyTorch": "1.11.0+cu113", "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 0x7fdb73c0d290>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fdb73c0d320>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fdb73c0d3b0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fdb73c0d440>", "_build": "<function ActorCriticPolicy._build at 0x7fdb73c0d4d0>", "forward": "<function ActorCriticPolicy.forward at 0x7fdb73c0d560>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fdb73c0d5f0>", "_predict": "<function ActorCriticPolicy._predict at 0x7fdb73c0d680>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fdb73c0d710>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fdb73c0d7a0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fdb73c0d830>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7fdb73be70c0>"}, "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": 4, "num_timesteps": 10002432, "_total_timesteps": 10000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1652359024.4056726, "learning_rate": 0.003, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWV9QAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJaAAAAAAAAAALrifD7bbn0/6bKcPu16o75DdRM/wcSHPgAAAAAAAAAAZpMEvSOZDj3T64o+Tn4bvi8yhD0g5RY9AAAAAAAAAACtLQW+0fiuPT2wlT4aC1K+CVKdvOIm0jwAAAAAAAAAAGZ4gTyHu6o+I6NlvAt4pb5MRFe8kH4uvQAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksESwiGlIwBQ5R0lFKULg=="}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYEAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwSFlIwBQ5R0lFKULg=="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.00024320000000011, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVNhAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIEf3a+invcECUhpRSlIwBbJRLyYwBdJRHQMIsMfb9If91fZQoaAZoCWgPQwi+wKxQpK9zQJSGlFKUaBVNMwFoFkdAwiyogQpWm3V9lChoBmgJaA9DCNkngGLkQHBAlIaUUpRoFU0oAmgWR0DCLXsOVgQZdX2UKGgGaAloD0MIfo/669VbcUCUhpRSlGgVTZQBaBZHQMItq4gA6uJ1fZQoaAZoCWgPQwieXb714QJmQJSGlFKUaBVN6ANoFkdAwi2s0CzTnnV9lChoBmgJaA9DCMbctYQ8FnBAlIaUUpRoFUvIaBZHQMIuHqfWcz91fZQoaAZoCWgPQwjDuYYZ2pZxQJSGlFKUaBVL4GgWR0DCLi0qhDgJdX2UKGgGaAloD0MIYw0XuSdnY0CUhpRSlGgVTegDaBZHQMIuXRJmNBF1fZQoaAZoCWgPQwgXD+85sDFvQJSGlFKUaBVNNQFoFkdAwi7Vl05lv3V9lChoBmgJaA9DCFLWbyam6G9AlIaUUpRoFU0QA2gWR0DCLz978ejmdX2UKGgGaAloD0MIqByTxf0NcUCUhpRSlGgVS91oFkdAwi9dfWtlqnV9lChoBmgJaA9DCIIBhA8l/nJAlIaUUpRoFUvuaBZHQMIvx9H2AXl1fZQoaAZoCWgPQwgWbvlIiktxQJSGlFKUaBVL/WgWR0DCL+nw9aEBdX2UKGgGaAloD0MI9z5VhYbBY0CUhpRSlGgVTegDaBZHQMIwXtgKF7F1fZQoaAZoCWgPQwiYUSy3NH1yQJSGlFKUaBVNFwFoFkdAwjBrPl+3IHV9lChoBmgJaA9DCIMZU7BGsXBAlIaUUpRoFUvxaBZHQMIwd/RE4Nt1fZQoaAZoCWgPQwjnyMovA39yQJSGlFKUaBVN5ANoFkdAwjCSAxSHd3V9lChoBmgJaA9DCO0OKQZICDBAlIaUUpRoFUunaBZHQMIwvig00nB1fZQoaAZoCWgPQwjYYyKl2e9wQJSGlFKUaBVL6mgWR0DCMNA/9pAVdX2UKGgGaAloD0MIYtwNovUjcUCUhpRSlGgVTQkBaBZHQMIw07y6MBJ1fZQoaAZoCWgPQwiQ9GkVfW1zQJSGlFKUaBVL0mgWR0DCMOZu63AmdX2UKGgGaAloD0MIdSLBVLNzcECUhpRSlGgVS9hoFkdAwjEQzxgAqHV9lChoBmgJaA9DCHAH6pRH2XJAlIaUUpRoFUvwaBZHQMIxLDJEH+t1fZQoaAZoCWgPQwjABdmyPG1wQJSGlFKUaBVNCwFoFkdAwjE6reZXuHV9lChoBmgJaA9DCK/QB8tYom1AlIaUUpRoFUvZaBZHQMIxPIIOYpl1fZQoaAZoCWgPQwgE6Pf92xRyQJSGlFKUaBVL/GgWR0DCMXXQ6ZH/dX2UKGgGaAloD0MInYAmwgZucUCUhpRSlGgVS/ZoFkdAwjGOMd92HXV9lChoBmgJaA9DCF8JpMSu9W1AlIaUUpRoFUvbaBZHQMIxkbGNrCZ1fZQoaAZoCWgPQwjqI/CH32FyQJSGlFKUaBVL1mgWR0DCMdA+lj3FdX2UKGgGaAloD0MIk+LjE3L3cUCUhpRSlGgVTQkBaBZHQMIyE0rkKeF1fZQoaAZoCWgPQwitpuuJ7rdyQJSGlFKUaBVNHAFoFkdAwjIYHTqjanV9lChoBmgJaA9DCGIQWDn06XJAlIaUUpRoFU3tAWgWR0DCMhogDA8CdX2UKGgGaAloD0MIwjHLngRDckCUhpRSlGgVTR8BaBZHQMIyVo73fyh1fZQoaAZoCWgPQwjr5XeajHRxQJSGlFKUaBVL+mgWR0DCMnwpnYg8dX2UKGgGaAloD0MIRbqfUxBVckCUhpRSlGgVS/NoFkdAwjJ/dPci4nV9lChoBmgJaA9DCDdV98jmV2xAlIaUUpRoFU0lAWgWR0DCMpI2ycCpdX2UKGgGaAloD0MIHHkgssj4cUCUhpRSlGgVS/BoFkdAwjK9vcafjHV9lChoBmgJaA9DCCv52F3gHXFAlIaUUpRoFUv4aBZHQMIy5Ah8pkR1fZQoaAZoCWgPQwiUFFgA0/hyQJSGlFKUaBVL3mgWR0DCMu5zFMqSdX2UKGgGaAloD0MIQ1Thz/CvckCUhpRSlGgVTQ4BaBZHQMIy7v114gR1fZQoaAZoCWgPQwi37uapzjNyQJSGlFKUaBVL4GgWR0DCMxUsDnvEdX2UKGgGaAloD0MI+kUJ+ksgcECUhpRSlGgVS+FoFkdAwjM5a/yoXXV9lChoBmgJaA9DCA/R6A6i1XBAlIaUUpRoFU0FAWgWR0DCM1UvRJEqdX2UKGgGaAloD0MIYqBrX0BecECUhpRSlGgVTQYBaBZHQMIzVj+rELp1fZQoaAZoCWgPQwjTvOMUXa9yQJSGlFKUaBVL5GgWR0DCM3FiBoVVdX2UKGgGaAloD0MI5WTiVsGockCUhpRSlGgVS+NoFkdAwjOVspoboHV9lChoBmgJaA9DCNeIYBzcg3FAlIaUUpRoFUvVaBZHQMIzqwj2SMd1fZQoaAZoCWgPQwhWDi2ynY9NQJSGlFKUaBVLkWgWR0DCM63557gLdX2UKGgGaAloD0MIKJtyhbc5ckCUhpRSlGgVS99oFkdAwjO5zmwJPnV9lChoBmgJaA9DCGlTdY+sF3JAlIaUUpRoFUvwaBZHQMIz/UHIIWx1fZQoaAZoCWgPQwjxg/Opo6RwQJSGlFKUaBVL6GgWR0DCNA57/n4gdX2UKGgGaAloD0MIPDPBcO6ccUCUhpRSlGgVS+doFkdAwjQSnhKlHnV9lChoBmgJaA9DCCvCTUaVKXJAlIaUUpRoFUv/aBZHQMI0GTEaVD91fZQoaAZoCWgPQwjaA63AkLdwQJSGlFKUaBVL4GgWR0DCNFGp6yB1dX2UKGgGaAloD0MI7ISX4BRycECUhpRSlGgVS8xoFkdAwjRe7/4qPXV9lChoBmgJaA9DCMybw7Xaom5AlIaUUpRoFUv1aBZHQMI0aktdzGR1fZQoaAZoCWgPQwiVfVcEP5NxQJSGlFKUaBVL9GgWR0DCNHRQxesxdX2UKGgGaAloD0MICd/7GzQ6ckCUhpRSlGgVS+hoFkdAwjSqBVdX1nV9lChoBmgJaA9DCG06AriZyHBAlIaUUpRoFUvlaBZHQMI0ta99MK11fZQoaAZoCWgPQwhdwwyNZ4FxQJSGlFKUaBVL2WgWR0DCNLxKjBVNdX2UKGgGaAloD0MIN23GaQgMcUCUhpRSlGgVS+9oFkdAwjTOdDIBBHV9lChoBmgJaA9DCAEW+fXDwGxAlIaUUpRoFUvyaBZHQMI1B6HKwIN1fZQoaAZoCWgPQwiV2LW9nX5xQJSGlFKUaBVL7mgWR0DCNRKt7rs0dX2UKGgGaAloD0MIrmLxm4JnckCUhpRSlGgVS+xoFkdAwjUZHf/FSHV9lChoBmgJaA9DCL00RYATJnBAlIaUUpRoFUveaBZHQMI1JksJ6Y51fZQoaAZoCWgPQwgudCUCVepvQJSGlFKUaBVL1WgWR0DCNWW54GD+dX2UKGgGaAloD0MIAYi7epW4cUCUhpRSlGgVS+VoFkdAwjV3jOs1bnV9lChoBmgJaA9DCHoAi/w6SnNAlIaUUpRoFUvdaBZHQMI1eqbSZ0F1fZQoaAZoCWgPQwglrfiGAoVxQJSGlFKUaBVL12gWR0DCNYZs0pEydX2UKGgGaAloD0MIf8LZrSVkcUCUhpRSlGgVS/JoFkdAwjXGRcNYsHV9lChoBmgJaA9DCD/mAwKdbW9AlIaUUpRoFUvWaBZHQMI1z0y57PZ1fZQoaAZoCWgPQwjSxhFrsWFyQJSGlFKUaBVL1mgWR0DCNdsnJDE4dX2UKGgGaAloD0MIGQRWDu2fckCUhpRSlGgVTQ4BaBZHQMI14T0HyEt1fZQoaAZoCWgPQwjJkGPr2TdxQJSGlFKUaBVL4mgWR0DCNhy68QI2dX2UKGgGaAloD0MITGvT2N5dcECUhpRSlGgVTQIBaBZHQMI2NVvl2eR1fZQoaAZoCWgPQwjFcHUARHNzQJSGlFKUaBVL1mgWR0DCNjcyHmA9dX2UKGgGaAloD0MIuyakNUZDckCUhpRSlGgVS/RoFkdAwjY8BEKE4HV9lChoBmgJaA9DCMQmMnOBDm5AlIaUUpRoFUvcaBZHQMI2ctu+AVh1fZQoaAZoCWgPQwjpYP2fgx9xQJSGlFKUaBVL0mgWR0DCNobFbVz7dX2UKGgGaAloD0MI9bhvtY5ZcECUhpRSlGgVS9poFkdAwjaRprULD3V9lChoBmgJaA9DCJmfG5oyCG9AlIaUUpRoFU03AWgWR0DCNrEUj9n9dX2UKGgGaAloD0MI0jWTb3YOcECUhpRSlGgVS+JoFkdAwjbP7NSqEXV9lChoBmgJaA9DCFch5SeV0XFAlIaUUpRoFUv4aBZHQMI29RtP5591fZQoaAZoCWgPQwhrD3uhwI9xQJSGlFKUaBVNGQFoFkdAwjcMAHVwxXV9lChoBmgJaA9DCPEqa5uibnBAlIaUUpRoFUvWaBZHQMI3EOq//Nt1fZQoaAZoCWgPQwgwaCEBI7ZsQJSGlFKUaBVL4GgWR0DCNzRX+2mYdX2UKGgGaAloD0MIpONqZFchc0CUhpRSlGgVS+5oFkdAwjdVtgrpaHV9lChoBmgJaA9DCKuUnuklz3FAlIaUUpRoFUvgaBZHQMI3aNQbdad1fZQoaAZoCWgPQwhnR6rvPCVxQJSGlFKUaBVL5WgWR0DCN292mpEQdX2UKGgGaAloD0MISYCaWnZJcUCUhpRSlGgVS9JoFkdAwjeHPeHi33V9lChoBmgJaA9DCN51NuQfwXFAlIaUUpRoFUvSaBZHQMI3pjg62fF1fZQoaAZoCWgPQwi4yagyDNBvQJSGlFKUaBVL7mgWR0DCN8U+RoysdX2UKGgGaAloD0MIMUEN30IncECUhpRSlGgVS+xoFkdAwjfpaNdZ73V9lChoBmgJaA9DCHAGf78YOnNAlIaUUpRoFU1FAWgWR0DCN/Jmukk9dX2UKGgGaAloD0MIM9yAzw8kckCUhpRSlGgVS+JoFkdAwjgDWf9P13V9lChoBmgJaA9DCDEKgsc33G5AlIaUUpRoFUvfaBZHQMI4HL30wrV1fZQoaAZoCWgPQwi5N79hootwQJSGlFKUaBVL32gWR0DCOD8SsbNsdX2UKGgGaAloD0MItCJqos/vb0CUhpRSlGgVS+loFkdAwjhLpKzzE3V9lChoBmgJaA9DCBnkLsIUL3FAlIaUUpRoFUvWaBZHQMI4Vo1DSgJ1fZQoaAZoCWgPQwi9GqA01CBwQJSGlFKUaBVL12gWR0DCOHFLnLaFdWUu"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 19536, "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": 4096, "n_epochs": 8, "clip_range": {":type:": "<class 'function'>", ":serialized:": "gAWVvwIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwNX2J1aWx0aW5fdHlwZZSTlIwKTGFtYmRhVHlwZZSFlFKUKGgCjAhDb2RlVHlwZZSFlFKUKEsBSwBLAUsBSxNDBIgAUwCUToWUKYwBX5SFlIxIL3Vzci9sb2NhbC9saWIvcHl0aG9uMy43L2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lIwEZnVuY5RLgEMCAAGUjAN2YWyUhZQpdJRSlH2UKIwLX19wYWNrYWdlX1+UjBhzdGFibGVfYmFzZWxpbmVzMy5jb21tb26UjAhfX25hbWVfX5SMHnN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi51dGlsc5SMCF9fZmlsZV9flIxIL3Vzci9sb2NhbC9saWIvcHl0aG9uMy43L2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaCB9lH2UKGgXaA6MDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgYjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz/JmZmZmZmahZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "system_info": {"OS": "Linux-5.4.188+-x86_64-with-Ubuntu-18.04-bionic #1 SMP Sun Apr 24 10:03:06 PDT 2022", "Python": "3.7.13", "Stable-Baselines3": "1.5.0", "PyTorch": "1.11.0+cu113", "GPU Enabled": "True", "Numpy": "1.21.6", "Gym": "0.21.0"}}
|
replay.mp4
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:a3d9a80b0ce5eadfebe0f601010743c2545537ff3ecaa458811348b3656e506e
|
3 |
+
size 217177
|
results.json
CHANGED
@@ -1 +1 @@
|
|
1 |
-
{"mean_reward":
|
|
|
1 |
+
{"mean_reward": 284.8629342696507, "std_reward": 16.56886588935504, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-05-12T15:21:22.398461"}
|