{
    "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 0x7e941c293400>",
        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7e941c293490>",
        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7e941c293520>",
        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7e941c2935b0>",
        "_build": "<function ActorCriticPolicy._build at 0x7e941c293640>",
        "forward": "<function ActorCriticPolicy.forward at 0x7e941c2936d0>",
        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7e941c293760>",
        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7e941c2937f0>",
        "_predict": "<function ActorCriticPolicy._predict at 0x7e941c293880>",
        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7e941c293910>",
        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7e941c2939a0>",
        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7e941c293a30>",
        "__abstractmethods__": "frozenset()",
        "_abc_impl": "<_abc._abc_data object at 0x7e941c437a80>"
    },
    "verbose": 1,
    "policy_kwargs": {},
    "num_timesteps": 1015808,
    "_total_timesteps": 1000000,
    "_num_timesteps_at_start": 0,
    "seed": null,
    "action_noise": null,
    "start_time": 1701358221242856347,
    "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": 248,
    "observation_space": {
        ":type:": "<class 'gymnasium.spaces.box.Box'>",
        ":serialized:": "gAWVcAIAAAAAAACMFGd5bW5hc2l1bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lGgFk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMDWJvdW5kZWRfYmVsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWCAAAAAAAAAABAQEBAQEBAZRoB4wCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksIhZSMAUOUdJRSlIwNYm91bmRlZF9hYm92ZZRoECiWCAAAAAAAAAABAQEBAQEBAZRoFEsIhZRoGHSUUpSMBl9zaGFwZZRLCIWUjANsb3eUaBAoliAAAAAAAAAAAAC0wgAAtMIAAKDAAACgwNsPScAAAKDAAAAAgAAAAICUaApLCIWUaBh0lFKUjARoaWdolGgQKJYgAAAAAAAAAAAAtEIAALRCAACgQAAAoEDbD0lAAACgQAAAgD8AAIA/lGgKSwiFlGgYdJRSlIwIbG93X3JlcHKUjFtbLTkwLiAgICAgICAgLTkwLiAgICAgICAgIC01LiAgICAgICAgIC01LiAgICAgICAgIC0zLjE0MTU5MjcgIC01LgogIC0wLiAgICAgICAgIC0wLiAgICAgICBdlIwJaGlnaF9yZXBylIxTWzkwLiAgICAgICAgOTAuICAgICAgICAgNS4gICAgICAgICA1LiAgICAgICAgIDMuMTQxNTkyNyAgNS4KICAxLiAgICAgICAgIDEuICAgICAgIF2UjApfbnBfcmFuZG9tlE51Yi4=",
        "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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"
    }
}