{
    "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 0x7fa3041909d0>",
        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fa304190a60>",
        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fa304190af0>",
        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fa304190b80>",
        "_build": "<function ActorCriticPolicy._build at 0x7fa304190c10>",
        "forward": "<function ActorCriticPolicy.forward at 0x7fa304190ca0>",
        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7fa304190d30>",
        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fa304190dc0>",
        "_predict": "<function ActorCriticPolicy._predict at 0x7fa304190e50>",
        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fa304190ee0>",
        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fa304190f70>",
        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fa304195040>",
        "__abstractmethods__": "frozenset()",
        "_abc_impl": "<_abc_data object at 0x7fa304187f60>"
    },
    "verbose": 1,
    "policy_kwargs": {
        ":type:": "<class 'dict'>",
        ":serialized:": "gAWVowAAAAAAAAB9lCiMDGxvZ19zdGRfaW5pdJRK/v///4wKb3J0aG9faW5pdJSJjA9vcHRpbWl6ZXJfY2xhc3OUjBN0b3JjaC5vcHRpbS5ybXNwcm9wlIwHUk1TcHJvcJSTlIwQb3B0aW1pemVyX2t3YXJnc5R9lCiMBWFscGhhlEc/764UeuFHrowDZXBzlEc+5Pi1iONo8YwMd2VpZ2h0X2RlY2F5lEsAdXUu",
        "log_std_init": -2,
        "ortho_init": false,
        "optimizer_class": "<class 'torch.optim.rmsprop.RMSprop'>",
        "optimizer_kwargs": {
            "alpha": 0.99,
            "eps": 1e-05,
            "weight_decay": 0
        }
    },
    "observation_space": {
        ":type:": "<class 'gym.spaces.box.Box'>",
        ":serialized:": "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",
        "dtype": "float32",
        "_shape": [
            28
        ],
        "low": "[-inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf\n -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf]",
        "high": "[inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf\n inf inf inf inf inf inf inf inf inf inf]",
        "bounded_below": "[False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False]",
        "bounded_above": "[False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False]",
        "_np_random": null
    },
    "action_space": {
        ":type:": "<class 'gym.spaces.box.Box'>",
        ":serialized:": "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",
        "dtype": "float32",
        "_shape": [
            8
        ],
        "low": "[-1. -1. -1. -1. -1. -1. -1. -1.]",
        "high": "[1. 1. 1. 1. 1. 1. 1. 1.]",
        "bounded_below": "[ True  True  True  True  True  True  True  True]",
        "bounded_above": "[ True  True  True  True  True  True  True  True]",
        "_np_random": null
    },
    "n_envs": 4,
    "num_timesteps": 2000000,
    "_total_timesteps": 2000000,
    "_num_timesteps_at_start": 0,
    "seed": null,
    "action_noise": null,
    "start_time": 1677337949447152718,
    "learning_rate": 0.00096,
    "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:": "gAWVdwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYEAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwSFlIwBQ5R0lFKULg=="
    },
    "_last_original_obs": {
        ":type:": "<class 'numpy.ndarray'>",
        ":serialized:": "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"
    },
    "_episode_num": 0,
    "use_sde": true,
    "sde_sample_freq": -1,
    "_current_progress_remaining": 0.0,
    "ep_info_buffer": {
        ":type:": "<class 'collections.deque'>",
        ":serialized:": "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"
    },
    "ep_success_buffer": {
        ":type:": "<class 'collections.deque'>",
        ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
    },
    "_n_updates": 62500,
    "n_steps": 8,
    "gamma": 0.99,
    "gae_lambda": 0.9,
    "ent_coef": 0.0,
    "vf_coef": 0.4,
    "max_grad_norm": 0.5,
    "normalize_advantage": false
}