{"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 0x7b95bdb111b0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7b95bdb11240>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7b95bdb112d0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7b95bdb11360>", "_build": "<function ActorCriticPolicy._build at 0x7b95bdb113f0>", "forward": "<function ActorCriticPolicy.forward at 0x7b95bdb11480>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7b95bdb11510>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7b95bdb115a0>", "_predict": "<function ActorCriticPolicy._predict at 0x7b95bdb11630>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7b95bdb116c0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7b95bdb11750>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7b95bdb117e0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7b95bdb148c0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 6898527, "_total_timesteps": 20000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1717670201498341766, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAAJrZSjuy5VE/XusbvvVJDL+2SKQ9HBMFvgAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksBSwiGlIwBQ5R0lFKULg=="}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdAAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYBAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwGFlIwBQ5R0lFKULg=="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": 0.6551168, "_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": 27332, "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": "Generator(PCG64)"}, "action_space": {":type:": "<class 'gymnasium.spaces.discrete.Discrete'>", ":serialized:": "gAWV2wAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgOjApfbnBfcmFuZG9tlE51Yi4=", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 1, "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, "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": "False", "Numpy": "1.25.2", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}