Updated the AI

README.md

@@ -16,7 +16,7 @@ model-index:
       type: LunarLander-v2
     metrics:
     - type: mean_reward
-      value: -662.98 +/- 107.41
+      value: 235.44 +/- 18.07
       name: mean_reward
       verified: false
 ---

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 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 0x7ac4fb82f880>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7ac4fb82f910>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7ac4fb82f9a0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7ac4fb82fa30>", "_build": "<function ActorCriticPolicy._build at 0x7ac4fb82fac0>", "forward": "<function ActorCriticPolicy.forward at 0x7ac4fb82fb50>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7ac4fb82fbe0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7ac4fb82fc70>", "_predict": "<function ActorCriticPolicy._predict at 0x7ac4fb82fd00>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7ac4fb82fd90>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7ac4fb82fe20>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7ac4fb82feb0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7ac4fc8c9480>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 4288, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1718910227760015963, "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": -0.6384000000000001, "_stats_window_size": 100, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWV3AAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpRHwEOQQnQY1pGMAWyUS6qMAXSUR0CYLh6rNnoQdX2UKGgGR8BHAzP8hs68aAdLv2gIR0CYLthL5AQhdX2UKGgGR8Bl9vTI/7iyaAdLzGgIR0CYL0sz2vjfdX2UKGgGR8BCxfUF0PpZaAdL1GgIR0CYL5O/L1VYdX2UKGgGR8BBbciwB5ooaAdL5WgIR0CYMC6VdHDrdX2UKGgGR8AzPidrftQbaAdL+WgIR0CYMOeQuEmIdWUu"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 56, "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": 0.9, "gae_lambda": 0.95, "ent_coef": 0.01, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 128, "n_epochs": 4, "clip_range": {":type:": "<class 'function'>", ":serialized:": "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"}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "system_info": {"OS": "Linux-6.1.85+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sun Apr 28 14:29:16 UTC 2024", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.3.0+cu121", "GPU Enabled": "True", "Numpy": "1.25.2", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}
+{"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 0x7ac4fb82f880>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7ac4fb82f910>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7ac4fb82f9a0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7ac4fb82fa30>", "_build": "<function ActorCriticPolicy._build at 0x7ac4fb82fac0>", "forward": "<function ActorCriticPolicy.forward at 0x7ac4fb82fb50>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7ac4fb82fbe0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7ac4fb82fc70>", "_predict": "<function ActorCriticPolicy._predict at 0x7ac4fb82fd00>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7ac4fb82fd90>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7ac4fb82fe20>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7ac4fb82feb0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7ac4fc8c9480>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1718911288674822308, "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": 328, "observation_space": {":type:": "<class 'gymnasium.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "bounded_below": "[ True  True  True  True  True  True  True  True]", "bounded_above": "[ True  True  True  True  True  True  True  True]", "_shape": [8], "low": "[-90.        -90.         -5.         -5.         -3.1415927  -5.\n  -0.         -0.       ]", "high": "[90.        90.         5.         5.         3.1415927  5.\n  1.         1.       ]", "low_repr": "[-90.        -90.         -5.         -5.         -3.1415927  -5.\n  -0.         -0.       ]", "high_repr": "[90.        90.         5.         5.         3.1415927  5.\n  1.         1.       ]", "_np_random": null}, "action_space": {":type:": "<class 'gymnasium.spaces.discrete.Discrete'>", ":serialized:": "gAWV2wAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgOjApfbnBfcmFuZG9tlE51Yi4=", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "n_steps": 1024, "gamma": 0.999, "gae_lambda": 0.95, "ent_coef": 0.01, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 128, "n_epochs": 4, "clip_range": {":type:": "<class 'function'>", ":serialized:": "gAWVxQIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTAvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUjARmdW5jlEuEQwIEAZSMA3ZhbJSFlCl0lFKUfZQojAtfX3BhY2thZ2VfX5SMGHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbpSMCF9fbmFtZV9flIwec3RhYmxlX2Jhc2VsaW5lczMuY29tbW9uLnV0aWxzlIwIX19maWxlX1+UjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjEwL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaB99lH2UKGgWaA2MDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgXjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz/JmZmZmZmahZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "system_info": {"OS": "Linux-6.1.85+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sun Apr 28 14:29:16 UTC 2024", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.3.0+cu121", "GPU Enabled": "True", "Numpy": "1.25.2", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}

ppo-LunarLander-v2.zip

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:a072eba69e76629841a89a33dc1f8abee3d93b4b7db7167bc1bbe9af7ae2f891
-size 144185
+oid sha256:f1245a426b1d4c27b56738bc76eeaee112cf4b3e738cb19e22c51fe9f776d41d
+size 148069

ppo-LunarLander-v2/data

@@ -21,17 +21,17 @@
     },
     "verbose": 1,
     "policy_kwargs": {},
-    "num_timesteps": 4288,
+    "num_timesteps": 1015808,
     "_total_timesteps": 1000000,
     "_num_timesteps_at_start": 0,
     "seed": null,
     "action_noise": null,
-    "start_time": 1718910227760015963,
+    "start_time": 1718911288674822308,
     "learning_rate": 0.0003,
     "tensorboard_log": null,
     "_last_obs": {
         ":type:": "<class 'numpy.ndarray'>",
-        ":serialized:": "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"
+        ":serialized:": "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"
     },
     "_last_episode_starts": {
         ":type:": "<class 'numpy.ndarray'>",
@@ -41,17 +41,17 @@
     "_episode_num": 0,
     "use_sde": false,
     "sde_sample_freq": -1,
-    "_current_progress_remaining": -0.6384000000000001,
+    "_current_progress_remaining": -0.015808000000000044,
     "_stats_window_size": 100,
     "ep_info_buffer": {
         ":type:": "<class 'collections.deque'>",
-        ":serialized:": "gAWV3AAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpRHwEOQQnQY1pGMAWyUS6qMAXSUR0CYLh6rNnoQdX2UKGgGR8BHAzP8hs68aAdLv2gIR0CYLthL5AQhdX2UKGgGR8Bl9vTI/7iyaAdLzGgIR0CYL0sz2vjfdX2UKGgGR8BCxfUF0PpZaAdL1GgIR0CYL5O/L1VYdX2UKGgGR8BBbciwB5ooaAdL5WgIR0CYMC6VdHDrdX2UKGgGR8AzPidrftQbaAdL+WgIR0CYMOeQuEmIdWUu"
+        ":serialized:": "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"
     },
     "ep_success_buffer": {
         ":type:": "<class 'collections.deque'>",
         ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
     },
-    "_n_updates": 56,
+    "_n_updates": 328,
     "observation_space": {
         ":type:": "<class 'gymnasium.spaces.box.Box'>",
         ":serialized:": "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",
@@ -78,7 +78,7 @@
     },
     "n_envs": 16,
     "n_steps": 1024,
-    "gamma": 0.9,
+    "gamma": 0.999,
     "gae_lambda": 0.95,
     "ent_coef": 0.01,
     "vf_coef": 0.5,

ppo-LunarLander-v2/policy.optimizer.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:62ef3832fa99cb698ae2e4a09d2cdb73a6092a206dd5be919778c22400755ff5
+oid sha256:9de3d0859e6c691feb286a913d6ca613c6ba91c5c412fcffffd67e0b9365ea98
 size 88362

ppo-LunarLander-v2/policy.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:6ed7ba0ae8011261e5efbd63eaa651734bdb823251fbf83ebb934732258cdf6e
+oid sha256:444153417c72b9e727bb6877b57b5bac310e42a7727a0ee583f70bbd7effe888
 size 43762

results.json

@@ -1 +1 @@
-{"mean_reward": -662.9839733000001, "std_reward": 107.40881881654828, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-06-20T19:08:46.816782"}
+{"mean_reward": 235.43945649999995, "std_reward": 18.067831952453098, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-06-20T19:43:02.283640"}