{
    "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 sde_net_arch: Network architecture for extracting features\n        when using gSDE. If None, the latent features from the policy will be used.\n        Pass an empty list to use the states as features.\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 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 0x7f82c8c90170>",
        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f82c8c90200>",
        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f82c8c90290>",
        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f82c8c90320>",
        "_build": "<function ActorCriticPolicy._build at 0x7f82c8c903b0>",
        "forward": "<function ActorCriticPolicy.forward at 0x7f82c8c90440>",
        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f82c8c904d0>",
        "_predict": "<function ActorCriticPolicy._predict at 0x7f82c8c90560>",
        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f82c8c905f0>",
        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f82c8c90680>",
        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f82c8c90710>",
        "__abstractmethods__": "frozenset()",
        "_abc_impl": "<_abc_data object at 0x7f82c8ce2300>"
    },
    "verbose": 1,
    "policy_kwargs": {},
    "observation_space": {
        ":type:": "<class 'gym.spaces.box.Box'>",
        ":serialized:": "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",
        "dtype": "float32",
        "_shape": [
            8
        ],
        "low": "[-inf -inf -inf -inf -inf -inf -inf -inf]",
        "high": "[inf inf inf inf inf inf inf inf]",
        "bounded_below": "[False False False False False False False False]",
        "bounded_above": "[False False False False False False False False]",
        "_np_random": null
    },
    "action_space": {
        ":type:": "<class 'gym.spaces.discrete.Discrete'>",
        ":serialized:": "gAWVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu",
        "n": 4,
        "_shape": [],
        "dtype": "int64",
        "_np_random": null
    },
    "n_envs": 16,
    "num_timesteps": 2506752,
    "_total_timesteps": 2500000,
    "_num_timesteps_at_start": 0,
    "seed": null,
    "action_noise": null,
    "start_time": 1652539645.219717,
    "learning_rate": 0.0003,
    "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:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="
    },
    "_last_original_obs": null,
    "_episode_num": 0,
    "use_sde": false,
    "sde_sample_freq": -1,
    "_current_progress_remaining": -0.0027007999999999477,
    "ep_info_buffer": {
        ":type:": "<class 'collections.deque'>",
        ":serialized:": "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"
    },
    "ep_success_buffer": {
        ":type:": "<class 'collections.deque'>",
        ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
    },
    "_n_updates": 612,
    "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
}