{
    "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 0x79654eb65240>",
        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x79654eb652d0>",
        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x79654eb65360>",
        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x79654eb653f0>",
        "_build": "<function ActorCriticPolicy._build at 0x79654eb65480>",
        "forward": "<function ActorCriticPolicy.forward at 0x79654eb65510>",
        "extract_features": "<function ActorCriticPolicy.extract_features at 0x79654eb655a0>",
        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x79654eb65630>",
        "_predict": "<function ActorCriticPolicy._predict at 0x79654eb656c0>",
        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x79654eb65750>",
        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x79654eb657e0>",
        "predict_values": "<function ActorCriticPolicy.predict_values at 0x79654eb65870>",
        "__abstractmethods__": "frozenset()",
        "_abc_impl": "<_abc._abc_data object at 0x79654eb07a00>"
    },
    "verbose": 1,
    "policy_kwargs": {},
    "num_timesteps": 1015808,
    "_total_timesteps": 1000000,
    "_num_timesteps_at_start": 0,
    "seed": null,
    "action_noise": null,
    "start_time": 1696276637957944240,
    "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": 372,
    "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:": "gAWV1QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCloCmgOjApfbnBfcmFuZG9tlE51Yi4=",
        "n": "4",
        "start": "0",
        "_shape": [],
        "dtype": "int64",
        "_np_random": null
    },
    "n_envs": 16,
    "n_steps": 2048,
    "gamma": 0.99,
    "gae_lambda": 0.95,
    "ent_coef": 0.0,
    "vf_coef": 0.5,
    "max_grad_norm": 0.5,
    "batch_size": 64,
    "n_epochs": 12,
    "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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"
    }
}