{
    "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 0x7fe1aea965f0>",
        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fe1aea96680>",
        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fe1aea96710>",
        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fe1aea967a0>",
        "_build": "<function ActorCriticPolicy._build at 0x7fe1aea96830>",
        "forward": "<function ActorCriticPolicy.forward at 0x7fe1aea968c0>",
        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fe1aea96950>",
        "_predict": "<function ActorCriticPolicy._predict at 0x7fe1aea969e0>",
        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fe1aea96a70>",
        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fe1aea96b00>",
        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fe1aea96b90>",
        "__abstractmethods__": "frozenset()",
        "_abc_impl": "<_abc_data object at 0x7fe1aeaf5570>"
    },
    "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": 524288,
    "_total_timesteps": 500000,
    "_num_timesteps_at_start": 0,
    "seed": null,
    "action_noise": null,
    "start_time": 1651952659.9492958,
    "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": -0.04857599999999995,
    "ep_info_buffer": {
        ":type:": "<class 'collections.deque'>",
        ":serialized:": "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"
    },
    "ep_success_buffer": {
        ":type:": "<class 'collections.deque'>",
        ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
    },
    "_n_updates": 160,
    "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": 10,
    "clip_range": {
        ":type:": "<class 'function'>",
        ":serialized:": "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"
    },
    "clip_range_vf": null,
    "normalize_advantage": true,
    "target_kl": null
}