{
    "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 0x78b506a06170>",
        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x78b506a06200>",
        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x78b506a06290>",
        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x78b506a06320>",
        "_build": "<function ActorCriticPolicy._build at 0x78b506a063b0>",
        "forward": "<function ActorCriticPolicy.forward at 0x78b506a06440>",
        "extract_features": "<function ActorCriticPolicy.extract_features at 0x78b506a064d0>",
        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x78b506a06560>",
        "_predict": "<function ActorCriticPolicy._predict at 0x78b506a065f0>",
        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x78b506a06680>",
        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x78b506a06710>",
        "predict_values": "<function ActorCriticPolicy.predict_values at 0x78b506a067a0>",
        "__abstractmethods__": "frozenset()",
        "_abc_impl": "<_abc._abc_data object at 0x78b506a09280>"
    },
    "verbose": 1,
    "policy_kwargs": {},
    "num_timesteps": 114688,
    "_total_timesteps": 100000,
    "_num_timesteps_at_start": 0,
    "seed": null,
    "action_noise": null,
    "start_time": 1697292596358752209,
    "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": -0.1468799999999999,
    "_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": 64,
    "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": 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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"
    }
}