nothing fun here

README.md

@@ -10,7 +10,7 @@ model-index:
   results:
   - metrics:
     - type: mean_reward
-      value: 209.18 +/- 39.09
+      value: 262.28 +/- 17.23
       name: mean_reward
     task:
       type: reinforcement-learning

config.json

@@ -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 0x7fc7465a9680>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fc7465a9710>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fc7465a97a0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fc7465a9830>", "_build": "<function ActorCriticPolicy._build at 0x7fc7465a98c0>", "forward": "<function ActorCriticPolicy.forward at 0x7fc7465a9950>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fc7465a99e0>", "_predict": "<function ActorCriticPolicy._predict at 0x7fc7465a9a70>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fc7465a9b00>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fc7465a9b90>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fc7465a9c20>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7fc7465ff180>"}, "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": 507904, "_total_timesteps": 500000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1651857345.4937458, "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:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////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": 124, "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-5.4.188+-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"}}
+{"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 0x7fc7465a9680>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fc7465a9710>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fc7465a97a0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fc7465a9830>", "_build": "<function ActorCriticPolicy._build at 0x7fc7465a98c0>", "forward": "<function ActorCriticPolicy.forward at 0x7fc7465a9950>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fc7465a99e0>", "_predict": "<function ActorCriticPolicy._predict at 0x7fc7465a9a70>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fc7465a9b00>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fc7465a9b90>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fc7465a9c20>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7fc7465ff180>"}, "verbose": 1, "policy_kwargs": {}, "observation_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "gAWVnwEAAAAAAACMDmd5bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lGgFk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMBl9zaGFwZZRLCIWUjANsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWIAAAAAAAAAAAAID/AACA/wAAgP8AAID/AACA/wAAgP8AAID/AACA/5RoCksIhZSMAUOUdJRSlIwEaGlnaJRoEiiWIAAAAAAAAAAAAIB/AACAfwAAgH8AAIB/AACAfwAAgH8AAIB/AACAf5RoCksIhZRoFXSUUpSMDWJvdW5kZWRfYmVsb3eUaBIolggAAAAAAAAAAAAAAAAAAACUaAeMAmIxlImIh5RSlChLA4wBfJROTk5K/////0r/////SwB0lGJLCIWUaBV0lFKUjA1ib3VuZGVkX2Fib3ZllGgSKJYIAAAAAAAAAAAAAAAAAAAAlGghSwiFlGgVdJRSlIwKX25wX3JhbmRvbZROdWIu", "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": 1651858494.9472606, "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:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////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": 496, "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": 128, "n_epochs": 8, "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"}}

dark-lander.zip

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:b7271e4c80c513f459878e7b296b3df30bc86e9411c48c94dbbf1e89c160ce55
-size 144024
+oid sha256:3316c26a9647560b98eca9bc71784bd72f83f3eab4f0d25ca679c17630516256
+size 144043

dark-lander/data

@@ -42,12 +42,12 @@
         "_np_random": null
     },
     "n_envs": 16,
-    "num_timesteps": 507904,
-    "_total_timesteps": 500000,
+    "num_timesteps": 1015808,
+    "_total_timesteps": 1000000,
     "_num_timesteps_at_start": 0,
     "seed": null,
     "action_noise": null,
-    "start_time": 1651857345.4937458,
+    "start_time": 1651858494.9472606,
     "learning_rate": 0.0003,
     "tensorboard_log": null,
     "lr_schedule": {
@@ -56,7 +56,7 @@
     },
     "_last_obs": {
         ":type:": "<class 'numpy.ndarray'>",
-        ":serialized:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAAG2U/D7TPCO+WxqcOtchu7xjbn86niSjvQAAgD8AAIA/7YKovuDtij62lPg8RwCBvkrDLr2aujA9AAAAAAAAAADedgy/u2RAvkIPFbvQAo24IqwbPko5/zgAAIA/AACAP+YFlr3DFRe6m7iKO+JZIDhARIA72h/WtwAAgD8AAIA/QI6JPY/aNbq+sqA7JKGMOIrHmzsSxre4AACAPwAAgD/AlB6+qdsMvLaIxbsKb/+5O2NePbsg1DoAAIA/AACAPwCxtj2kkDK5HjOHOY9pgbY04TG7ei2huAAAgD8AAIA/k98cvjx5Mj5Ogxg8lXeNvntXpD1WZlW+AAAAAAAAAAAQkqo+td4aPp40Dz5DBmm+0uM+vps9hL0AAAAAAAAAANqPRz4fIOc87sTGOMl7rjeS34A+/N0duAAAgD8AAIA/zfM6vUhB1zm2UaY6VZi4NT2ko7uVRci5AACAPwAAgD/NkzM9j9Zsuo0/BroZxm61OeW2Oc3VGTkAAIA/AACAP/pYTD4Klls8M39POxQYeDnKzOI9i3F8ugAAgD8AAIA/QM8vvttUr7yf+Z29GmhNvBBfHD4K7CA9AACAPwAAgD9zmKk+B2UdvbbdlrsTnCs6qGhMvuJT4DoAAAAAAACAP5qVr7spTH+63sj4OyRVmjegDgu7W7dWNgAAgD8AAIA/lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksQSwiGlIwBQ5R0lFKULg=="
+        ":serialized:": "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"
     },
     "_last_episode_starts": {
         ":type:": "<class 'numpy.ndarray'>",
@@ -69,21 +69,21 @@
     "_current_progress_remaining": -0.015808000000000044,
     "ep_info_buffer": {
         ":type:": "<class 'collections.deque'>",
-        ":serialized:": "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"
+        ":serialized:": "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"
     },
     "ep_success_buffer": {
         ":type:": "<class 'collections.deque'>",
         ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
     },
-    "_n_updates": 124,
+    "_n_updates": 496,
     "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,
+    "batch_size": 128,
+    "n_epochs": 8,
     "clip_range": {
         ":type:": "<class 'function'>",
         ":serialized:": "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"

dark-lander/policy.optimizer.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:ba4bacefec1a112b4a65eb340915986fe665a419c62614b3e8b5168616569bb5
+oid sha256:199f06c4b7faaaf9b8c9502fb5d3bd12a9aacefc18689e4dfcc4f842bf82912e
 size 84829

dark-lander/policy.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:41f019234b6534fd2b93af34b97ee0c167731945130b20255b83d932c24953ce
+oid sha256:61c38aa110bad06170be9d3f2990c070371b0655ebc9606702b98367903acfea
 size 43201

replay.mp4

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:0b0ec7be94fd20c41680a659f09eb6d327ddf2437205ada6e3ac558ab8a36e32
-size 236962
+oid sha256:d2aaee53045af52f1082fdeba098bee649a0eba03455b24c590e093076d5c535
+size 221676

results.json

@@ -1 +1 @@
-{"mean_reward": 209.17594546315317, "std_reward": 39.0902158582097, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-05-06T17:30:07.706936"}
+{"mean_reward": 262.27950906907364, "std_reward": 17.233154041999754, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-05-06T18:00:18.552409"}