8th lunar lander to push

README.md

@@ -16,7 +16,7 @@ model-index:
       type: LunarLander-v2
     metrics:
     - type: mean_reward
-      value: 284.95 +/- 18.85
+      value: 273.95 +/- 26.62
       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 0x780045866560>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7800458665f0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x780045866680>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x780045866710>", "_build": "<function ActorCriticPolicy._build at 0x7800458667a0>", "forward": "<function ActorCriticPolicy.forward at 0x780045866830>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7800458668c0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x780045866950>", "_predict": "<function ActorCriticPolicy._predict at 0x7800458669e0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x780045866a70>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x780045866b00>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x780045866b90>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x78004586c040>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1705963590825022099, "learning_rate": 0.0005248111544143684, "tensorboard_log": null, "_last_obs": null, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAEAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////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:": "gAWV4gsAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpRHQHG9I7zTWoaMAWyUS8GMAXSUR0C1jzDs+mm+dX2UKGgGR0Bx3NXiiqQzaAdLz2gIR0C1jzPoFFDwdX2UKGgGR0By+Jmdy1eCaAdLu2gIR0C1jz2aH9FXdX2UKGgGR0BxwGpsGgSOaAdLpmgIR0C1j0EMG5c1dX2UKGgGR0BxjWK3uuzQaAdLxmgIR0C1j1unMt9QdX2UKGgGR0BxpQlnh86WaAdLtGgIR0C1j4x+8XendX2UKGgGR0BySgCjk+5faAdL1GgIR0C1j6S4J/oadX2UKGgGR0Bt0cGs3hn8aAdLu2gIR0C1j7YZAIIGdX2UKGgGR0BxUEE6kqMFaAdLuGgIR0C1j/lk+X7cdX2UKGgGR0Bx85ylvZRLaAdLzGgIR0C1kANdu5z6dX2UKGgGR0BypZqN6w+uaAdLtWgIR0C1kAfo/zJ7dX2UKGgGR0Bzr3BnBciXaAdL0mgIR0C1kBH+VC5VdX2UKGgGR0BwDd+d9UjtaAdLtmgIR0C1kBDollbvdX2UKGgGR0ByYfD3ueBhaAdLw2gIR0C1kC8b70nPdX2UKGgGR0Bxrdc/t6X0aAdLq2gIR0C1kEfKISDidX2UKGgGR0BxA9MRHww1aAdLtmgIR0C1kEv38GcGdX2UKGgGR0Bxx/ZElVtGaAdLxmgIR0C1pwjSw4bTdX2UKGgGR0ByAXxd6cAjaAdLwmgIR0C1pw6gIyCWdX2UKGgGR0BwipS75Ec9aAdLtGgIR0C1pxjp5eJIdX2UKGgGR0ByPmVVxS5zaAdLnGgIR0C1pz0LlV94dX2UKGgGR0BxcsudwvQGaAdLlmgIR0C1p0W2b5M2dX2UKGgGR0B0Ax+G47RwaAdL1GgIR0C1p3i5Zr57dX2UKGgGR0BumtkH2RJVaAdLr2gIR0C1p7OyquKXdX2UKGgGR0BxBVlZowmFaAdLtmgIR0C1p7Z9iMHbdX2UKGgGR0Bx1vXTVlPKaAdNuAFoCEdAtae5IbwSanV9lChoBkdAcB5rxAjY7WgHS6VoCEdAtafQ2tMfzXV9lChoBkdAcc2NbkfcOGgHS8FoCEdAtafUbIcR2HV9lChoBkdAcIfRO1v2oWgHS8NoCEdAtaffnbItDnV9lChoBkdAcjEnwXqJM2gHS9BoCEdAtaf0QtjCpHV9lChoBkdAcXNl/pdKNGgHS7RoCEdAtaf+d4FA3XV9lChoBkdAUfrQSi/O+2gHS6poCEdAtagJKNAC4nV9lChoBkdAcgnSgoPTX2gHS7FoCEdAtagYF0PpZHV9lChoBkdAcnBtO2y9mGgHS8hoCEdAtage/N7jUHV9lChoBkdAcVSo7V8TjGgHS71oCEdAtagws3AEdXV9lChoBkdAcgUWhh6SkmgHS51oCEdAtahgeHSF5HV9lChoBkdAdAYkSmIj4mgHS9VoCEdAtaiBmRNh3XV9lChoBkdAcxhEvTPSlWgHS91oCEdAtaiFFEy+H3V9lChoBkdAboJ7el9Br2gHS6hoCEdAtaiudy1eB3V9lChoBkdAcaiY3vQWvmgHS8JoCEdAtajR7JGOMnV9lChoBkdAcaXeE7GNrGgHS7toCEdAtajnpSrHVHV9lChoBkdAcHwlzltCRmgHS6doCEdAtaj29bor4HV9lChoBkdAcljpn6Eal2gHS8poCEdAtakBGiHqNnV9lChoBkdAcuzrhisnzGgHS+RoCEdAtakMH5aePXV9lChoBkdAcuqvLowEhmgHS8doCEdAtakdId2gWnV9lChoBkdAcsOJQ+EAYGgHTTQDaAhHQLWpHogFHJ91fZQoaAZHQHBi1HavicZoB0vAaAhHQLWpJyCnP3V1fZQoaAZHQHLrowh4dIZoB0vgaAhHQLWpK3hXKbN1fZQoaAZHQHHacV1wHZ9oB0uqaAhHQLWpL/X5FgF1fZQoaAZHQHJftxAB1cNoB0vOaAhHQLWpRLYwqRV1fZQoaAZHQHISZlFtsN5oB0vNaAhHQLWpSeuFHrh1fZQoaAZHQHCm2pEQXhxoB0ufaAhHQLWpZ/h2nsN1fZQoaAZHQHA5j9GZuyhoB0u7aAhHQLWpbPrv9cd1fZQoaAZHQHMX3VwxWT5oB0vRaAhHQLWppRf4REp1fZQoaAZHQHQieQp4KQdoB0vlaAhHQLWp8yULUkR1fZQoaAZHQHMQL5AQg9xoB0vDaAhHQLWp9Vy3kPt1fZQoaAZHQHN5MWbgCOpoB0vRaAhHQLWp94/NZ/11fZQoaAZHQHJW10cOskpoB0uyaAhHQLWp/hEBsAN1fZQoaAZHQHMuqwIMSbpoB0vLaAhHQLWqDedCmdl1fZQoaAZHQHQlwWSEDhdoB0u8aAhHQLWqJD4QBgh1fZQoaAZHQHIS84LkS29oB0vXaAhHQLWqJbDdgv11fZQoaAZHQHItKYVqN6xoB0u6aAhHQLWqJow22oh1fZQoaAZHQHJOV4HHFP1oB0vMaAhHQLWqL/smfGx1fZQoaAZHQHDttilSCOFoB0uwaAhHQLWqOW5Yoy91fZQoaAZHQHHDnWOIZZVoB0vUaAhHQLWqOzlLeyl1fZQoaAZHQHRZd/8VHnVoB0vFaAhHQLWqOZ9uxbB1fZQoaAZHQHCnf8MuvlloB0vEaAhHQLWqS6/7BO51fZQoaAZHQHNWcOskpqhoB0u9aAhHQLWqZXSSeRR1fZQoaAZHQHIJ1Y+0PYpoB0vIaAhHQLWqeHqu8sd1fZQoaAZHQHEoMA7xNItoB0vMaAhHQLWqup1RtP51fZQoaAZHQHJnRpQDV6NoB0uqaAhHQLWq0W56MR91fZQoaAZHQHFPIgRsdktoB0uwaAhHQLWq5mHP/rB1fZQoaAZHQHCS5ZKWcBloB0u9aAhHQLWq8Km8/Ux1fZQoaAZHQHGkdoSL61toB0vKaAhHQLWrA/iHZbp1fZQoaAZHQHNJ2o3rD65oB0u+aAhHQLWrCky1uzh1fZQoaAZHQHGRk34sVcloB0upaAhHQLWrEk1Mue11fZQoaAZHQHHKyKvV3EBoB0u9aAhHQLWrKHh0heR1fZQoaAZHQHF3fms/6ftoB0uzaAhHQLWrN/iYLLJ1fZQoaAZHQHHT+B6KLsNoB0vFaAhHQLWrPdsBQvZ1fZQoaAZHQHGxYczZYgdoB0vPaAhHQLWrTiKiwjd1fZQoaAZHQHBq94mkWRBoB0vFaAhHQLWrV2uxKQJ1fZQoaAZHQHOdQx33YcxoB0vFaAhHQLWrWZ1V5rx1fZQoaAZHQHJfTeCTUy5oB0u3aAhHQLWrfe+23KB1fZQoaAZHQHNIAx33YcxoB0vZaAhHQLWrkoP07Kd1fZQoaAZHQHD/USuhbnpoB0vGaAhHQLWrsCfpUxV1fZQoaAZHQHGg9+CsfaJoB0u1aAhHQLWr5yRjjJd1fZQoaAZHQHCdWwRoRI1oB0uxaAhHQLWsALmZE2J1fZQoaAZHQHC3w3kxREZoB0u1aAhHQLWsIW/ag291fZQoaAZHQHIwqUaAFxJoB0uoaAhHQLWsOJEYwZh1fZQoaAZHQHPSojKPn0VoB0uwaAhHQLWsTwR5C4V1fZQoaAZHQHHIZ2IO6NFoB0vKaAhHQLWsUtcfNiZ1fZQoaAZHQG/oue8PFvRoB0uiaAhHQLWsVb5/LDB1fZQoaAZHQHHSOWrwOONoB0vMaAhHQLWscJHiFTN1fZQoaAZHQHC96dpZfUpoB0vCaAhHQLWsg+LFXJZ1fZQoaAZHQHJ5OWa+evpoB0u4aAhHQLWsk/nGKht1fZQoaAZHQHJzjRQaaThoB0vKaAhHQLWsopUgjhV1fZQoaAZHQHPd+2mYSg5oB0vAaAhHQLWsqtMfzSV1fZQoaAZHQHBq4R28qWloB0ulaAhHQLWsu2l2vB91fZQoaAZHQHHmZ/G2kSFoB0vRaAhHQLWs9qj8DSx1fZQoaAZHQHNr8xsVLzxoB0voaAhHQLWs+FF2FFl1fZQoaAZHQHLZAmmce8xoB0vDaAhHQLWtFNIsiB51ZS4="}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 620, "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:": "gAWV/QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgLjAJpOJSJiIeUUpQoSwNoD05OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "n_steps": 1024, "gamma": 0.9980331419912533, "gae_lambda": 0.9732726375562474, "ent_coef": 0.0019277118336484737, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 32, "n_epochs": 10, "clip_range": {":type:": "<class 'function'>", ":serialized:": "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"}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "system_info": {"OS": "Linux-6.1.58+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sat Nov 18 15:31:17 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.1.0+cu121", "GPU Enabled": "True", "Numpy": "1.23.5", "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 0x7f6b29a65870>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f6b29a65900>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f6b29a65990>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f6b29a65a20>", "_build": "<function ActorCriticPolicy._build at 0x7f6b29a65ab0>", "forward": "<function ActorCriticPolicy.forward at 0x7f6b29a65b40>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f6b29a65bd0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f6b29a65c60>", "_predict": "<function ActorCriticPolicy._predict at 0x7f6b29a65cf0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f6b29a65d80>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f6b29a65e10>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f6b29a65ea0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f6b29c584c0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 3014656, "_total_timesteps": 3000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1706022743938973631, "learning_rate": 0.0005248111544143684, "tensorboard_log": null, "_last_obs": null, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAABAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.004885333333333408, "_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": 1840, "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:": "gAWV/QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgLjAJpOJSJiIeUUpQoSwNoD05OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "n_steps": 1024, "gamma": 0.9980331419912533, "gae_lambda": 0.9732726375562474, "ent_coef": 0.0019277118336484737, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 32, "n_epochs": 10, "clip_range": {":type:": "<class 'function'>", ":serialized:": "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"}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "system_info": {"OS": "Linux-6.1.58+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sat Nov 18 15:31:17 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.1.0+cu121", "GPU Enabled": "True", "Numpy": "1.23.5", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}

ppo-LunarLander-v2-13.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e63283f1a11e7997e922c30414af49e06b10baa5a200d38bd0c471b60191444d
+size 147258

ppo-LunarLander-v2-13/_stable_baselines3_version

@@ -0,0 +1 @@
+2.0.0a5

ppo-LunarLander-v2-13/data

@@ -0,0 +1,96 @@
+{
+    "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 0x7f6b29a65870>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f6b29a65900>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f6b29a65990>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f6b29a65a20>",
+        "_build": "<function ActorCriticPolicy._build at 0x7f6b29a65ab0>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7f6b29a65b40>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f6b29a65bd0>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f6b29a65c60>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7f6b29a65cf0>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f6b29a65d80>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f6b29a65e10>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f6b29a65ea0>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x7f6b29c584c0>"
+    },
+    "verbose": 1,
+    "policy_kwargs": {},
+    "num_timesteps": 3014656,
+    "_total_timesteps": 3000000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1706022743938973631,
+    "learning_rate": 0.0005248111544143684,
+    "tensorboard_log": null,
+    "_last_obs": null,
+    "_last_episode_starts": {
+        ":type:": "<class 'numpy.ndarray'>",
+        ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAABAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="
+    },
+    "_last_original_obs": null,
+    "_episode_num": 0,
+    "use_sde": false,
+    "sde_sample_freq": -1,
+    "_current_progress_remaining": -0.004885333333333408,
+    "_stats_window_size": 100,
+    "ep_info_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "gAWV4QsAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpRHQHKj/ykKu0WMAWyUS6SMAXSUR0C16U8riEQHdX2UKGgGR0BzP4K4QSSNaAdLwmgIR0C1/w2Y0EX+dX2UKGgGR0Bx+DU9ZA6daAdL8WgIR0C1/xRHskY5dX2UKGgGR0BwgqzyBkI5aAdLnmgIR0C1/xPCyhSMdX2UKGgGR0BxIO8f3evZaAdLl2gIR0C1/yZ8a4tpdX2UKGgGR0BwLC717IDHaAdLnGgIR0C1/ytkFwDOdX2UKGgGR0ByO/SmZVn3aAdLzWgIR0C1/y5sfq5cdX2UKGgGR0ByQltelbeNaAdLsWgIR0C1/zK5sj3VdX2UKGgGR0Bw2qi7CiyqaAdLj2gIR0C1/zT8+A3DdX2UKGgGR0By6HvsqrimaAdLv2gIR0C1/0yvC/GmdX2UKGgGR0BzSlT987ZGaAdLq2gIR0C1/1Epy6tldX2UKGgGR0BwxTeSB9ThaAdLhWgIR0C1/1ifg75mdX2UKGgGR0BxsDM7lq8EaAdLkGgIR0C1/2EYXO4YdX2UKGgGR0Bx1uDHwPRRaAdLrGgIR0C1/6hVuJk5dX2UKGgGR0BH2b1RLsa9aAdLU2gIR0C1/87UgB91dX2UKGgGR0Bx3UP1+RYBaAdLtWgIR0C1/9EA5q/NdX2UKGgGR0BxpbSmZVn3aAdLpmgIR0C1/+E+gUUPdX2UKGgGR0BxNlGnXNC7aAdLk2gIR0C1/+JNTLntdX2UKGgGR0ByqkZ62OQyaAdLumgIR0C1/+WjTKDDdX2UKGgGR0Bwf1fYzzmPaAdLmmgIR0C1//hQBPsSdX2UKGgGR0BwoM+qzZ6EaAdLp2gIR0C2AAFNDc/MdX2UKGgGR0Bz54ZpBX0YaAdLumgIR0C2AAHDaXa8dX2UKGgGR0ByO9ccENe/aAdLv2gIR0C2AAhhhH9WdX2UKGgGR0BzNrF4s3AEaAdLrGgIR0C2ABEsrd30dX2UKGgGR0BzIneVLSNPaAdLsWgIR0C2ABCx3V0+dX2UKGgGR0Bx8KWmgrYoaAdLq2gIR0C2ACe7YkE+dX2UKGgGR0ByxcWTHKfWaAdLuGgIR0C2AD1RceKbdX2UKGgGR0Bzb6jJuEVWaAdLvmgIR0C2AFJflZHNdX2UKGgGR0Byyo99tuUEaAdLnWgIR0C2AHvqxC6ZdX2UKGgGR0BwnYNWluWKaAdLk2gIR0C2AJORoysTdX2UKGgGR0ByatRBNVR2aAdLk2gIR0C2AMRIjGDMdX2UKGgGR0BxR+n5zo2XaAdLq2gIR0C2ANmuLaVVdX2UKGgGR0Bytsa/ATIvaAdLvWgIR0C2AN7AHmihdX2UKGgGR0ByyLDjzZpSaAdLmGgIR0C2AN7noxHodX2UKGgGR0BzC9C8e0XxaAdLt2gIR0C2AO3Y6GQCdX2UKGgGR0BxgNqoIfKZaAdLh2gIR0C2APq/Zdv9dX2UKGgGR0BxVvJGOMl1aAdLpGgIR0C2AQBHskY5dX2UKGgGR0B0Wh7qptJnaAdLxWgIR0C2AQaLwWnCdX2UKGgGR0BEOR/d69kCaAdLUmgIR0C2AQkZaV2SdX2UKGgGR0ByiAeaKDTSaAdLtGgIR0C2ARHjhky2dX2UKGgGR0BzxFS0jTrnaAdLrmgIR0C2ARz3mFJydX2UKGgGR0ByVrDej2zwaAdLsWgIR0C2ASD+vQnhdX2UKGgGR0Bu9ClnAZbZaAdLi2gIR0C2ATMdDIBBdX2UKGgGR0ByClA0Kqn4aAdLomgIR0C2AUMyrPt2dX2UKGgGR0ByRFjhDPWyaAdLiGgIR0C2AYJVKf4AdX2UKGgGR0BxFLPjXFtLaAdLtWgIR0C2Ahz1K5CodX2UKGgGR0BypSHuZ1FIaAdLkGgIR0C2AiDR+jM3dX2UKGgGR0BzKYx1xKg7aAdLlmgIR0C2Ah+3pfQbdX2UKGgGR0ByiFfsu3+daAdLnmgIR0C2Ailr/KhddX2UKGgGR0BxwuWw/xDtaAdLtmgIR0C2AjK8pTdddX2UKGgGR0Bw6oUg0TDgaAdLoWgIR0C2AjlWCEpRdX2UKGgGR0BzZbbsWweOaAdLuWgIR0C2Aj2rCFbndX2UKGgGR0BzS2gGr0aqaAdLvWgIR0C2AkWL5ylvdX2UKGgGR0BzYKtvGZNPaAdLnmgIR0C2AkwWN3nqdX2UKGgGR0Byp+5BkZrIaAdLwGgIR0C2Alh1klNUdX2UKGgGR0BymTcJtzjnaAdLu2gIR0C2Alxgy/KydX2UKGgGR0B0IzQhOgxraAdLuWgIR0C2AoEl3QlbdX2UKGgGR0Bziu3solUqaAdLqmgIR0C2AortZ3cIdX2UKGgGR0BzD2K64Ds/aAdLtWgIR0C2Ao2VZ9uxdX2UKGgGR0By14NBnjABaAdLo2gIR0C2Ari35N48dX2UKGgGR0BM6Qjt5UtJaAdLXmgIR0C2AsnymQ8wdX2UKGgGR0BxxJXT3IuHaAdLh2gIR0C2Aw3XZoPDdX2UKGgGR0Bv96/9Hc1waAdN0ANoCEdAtgMRCu2ZzHV9lChoBkdAcilHUMG5c2gHS5BoCEdAtgMbRRdhRnV9lChoBkdAcePy2hIvrWgHS4VoCEdAtgNAzP8htHV9lChoBkdAc2VKKpDNQmgHS6JoCEdAtgNHLIPsiXV9lChoBkdAcwnez2OAAmgHS5hoCEdAtgNHH7xd6nV9lChoBkdAcRNOuaF23mgHS6FoCEdAtgNOlhw2l3V9lChoBkdAbvmH446wMmgHS5NoCEdAtgNX+Lm6oXV9lChoBkdAcbMJYT0xumgHS7toCEdAtgOCohpxm3V9lChoBkdAcvLJ/G2kSGgHS7RoCEdAtgOH9rGipXV9lChoBkdAcwOgnc+JQGgHS7loCEdAtgOKSX+l03V9lChoBkdAcQE55JK8MGgHS6BoCEdAtgOXpKSPl3V9lChoBkdAcVTGbCrLhmgHS6toCEdAtgOyg7HQyHV9lChoBkdAcemUYsNDt2gHS6RoCEdAtgPYofCAMHV9lChoBkdAcco1RceKbmgHS8VoCEdAtgPjmMfignV9lChoBkdAcXHfD1oQF2gHS7FoCEdAtgP2pIczZnV9lChoBkdAcRinUlRgqmgHS4hoCEdAtgP3b5/LDHV9lChoBkdAcnDgyM1jzGgHS59oCEdAtgQPdfsu4HV9lChoBkdAbyZ3ljmSyWgHS5JoCEdAtgQwMmWt2nV9lChoBkdAcmp5VOsT4GgHS55oCEdAtgQ0n2Iwd3V9lChoBkdAcuy+LWI42mgHS7hoCEdAtgQ2E8JUpHV9lChoBkdAcR+iNKh+OWgHS6ZoCEdAtgQ9z3h4uHV9lChoBkdAcd+4Pf8/EGgHS7FoCEdAtgRIcJdB0XV9lChoBkdAcoNiyIHkcWgHS5BoCEdAtgRQ1dgOSXV9lChoBkdAcYMh2W6bv2gHS5FoCEdAtgRQg+yJK3V9lChoBkdAck6CK77KrGgHS7NoCEdAtgRSrgflqHV9lChoBkdAcAcC0ngHeWgHS6NoCEdAtgRhGPPszHV9lChoBkdAb7rVnVXmvGgHS5loCEdAtgRjZIxxk3V9lChoBkdAbvKKVpsXSGgHS5poCEdAtgR4tTUAk3V9lChoBkdAcNT1Muez2WgHS6toCEdAtgSmLn9vTHV9lChoBkdAcajDE3sHB2gHS5VoCEdAtgSpYHPeHnV9lChoBkdAcabhfjS5RWgHS7BoCEdAtgTQPpY9xXV9lChoBkdAcuGs+3YthGgHS8BoCEdAtgTQAwPAf3V9lChoBkdAcsOfcvduYWgHS6NoCEdAtgUE0sOG03V9lChoBkdAcSPpPykKu2gHS6loCEdAtgUInkT6BXV9lChoBkdAdGjavRqoImgHS8toCEdAtgUQ5jpcHHV9lChoBkdAcxVQsPJ7s2gHS5VoCEdAtgUSo3rD63V9lChoBkdAcIoikwevIWgHS5loCEdAtgUV1Ng0CXV9lChoBkdAc35W3Sa3JGgHS7BoCEdAtgUe2c8Tz3VlLg=="
+    },
+    "ep_success_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
+    },
+    "_n_updates": 1840,
+    "observation_space": {
+        ":type:": "<class 'gymnasium.spaces.box.Box'>",
+        ":serialized:": "gAWVdgIAAAAAAACMFGd5bW5hc2l1bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lIwFZHR5cGWUk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMDWJvdW5kZWRfYmVsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWCAAAAAAAAAABAQEBAQEBAZRoCIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksIhZSMAUOUdJRSlIwNYm91bmRlZF9hYm92ZZRoESiWCAAAAAAAAAABAQEBAQEBAZRoFUsIhZRoGXSUUpSMBl9zaGFwZZRLCIWUjANsb3eUaBEoliAAAAAAAAAAAAC0wgAAtMIAAKDAAACgwNsPScAAAKDAAAAAgAAAAICUaAtLCIWUaBl0lFKUjARoaWdolGgRKJYgAAAAAAAAAAAAtEIAALRCAACgQAAAoEDbD0lAAACgQAAAgD8AAIA/lGgLSwiFlGgZdJRSlIwIbG93X3JlcHKUjFtbLTkwLiAgICAgICAgLTkwLiAgICAgICAgIC01LiAgICAgICAgIC01LiAgICAgICAgIC0zLjE0MTU5MjcgIC01LgogIC0wLiAgICAgICAgIC0wLiAgICAgICBdlIwJaGlnaF9yZXBylIxTWzkwLiAgICAgICAgOTAuICAgICAgICAgNS4gICAgICAgICA1LiAgICAgICAgIDMuMTQxNTkyNyAgNS4KICAxLiAgICAgICAgIDEuICAgICAgIF2UjApfbnBfcmFuZG9tlE51Yi4=",
+        "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:": "gAWV/QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgLjAJpOJSJiIeUUpQoSwNoD05OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu",
+        "n": "4",
+        "start": "0",
+        "_shape": [],
+        "dtype": "int64",
+        "_np_random": null
+    },
+    "n_envs": 16,
+    "n_steps": 1024,
+    "gamma": 0.9980331419912533,
+    "gae_lambda": 0.9732726375562474,
+    "ent_coef": 0.0019277118336484737,
+    "vf_coef": 0.5,
+    "max_grad_norm": 0.5,
+    "batch_size": 32,
+    "n_epochs": 10,
+    "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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"
+    }
+}

ppo-LunarLander-v2-13/policy.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:7b3a4db9ab1aee2e765b63f91741e5532a65bee6801299d30e963332a328ecd5
+size 88490

ppo-LunarLander-v2-13/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e060f7b98598e7cd7d8537e85ecd10ea46b8a0bda9ebb2c2374932320164ccab
+size 43762

ppo-LunarLander-v2-13/pytorch_variables.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0c35cea3b2e60fb5e7e162d3592df775cd400e575a31c72f359fb9e654ab00c5
+size 864

ppo-LunarLander-v2-13/system_info.txt

@@ -0,0 +1,9 @@
+- OS: Linux-6.1.58+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sat Nov 18 15:31:17 UTC 2023
+- Python: 3.10.12
+- Stable-Baselines3: 2.0.0a5
+- PyTorch: 2.1.0+cu121
+- GPU Enabled: True
+- Numpy: 1.23.5
+- Cloudpickle: 2.2.1
+- Gymnasium: 0.28.1
+- OpenAI Gym: 0.25.2

results.json

@@ -1 +1 @@
-{"mean_reward": 284.95021846810073, "std_reward": 18.851357674875093, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-01-22T23:23:26.085781"}
+{"mean_reward": 273.95341478651227, "std_reward": 26.61744740347847, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-01-23T16:47:04.729537"}