{
    "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 0x7f310239c040>",
        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f310239c0d0>",
        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f310239c160>",
        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f310239c1f0>",
        "_build": "<function ActorCriticPolicy._build at 0x7f310239c280>",
        "forward": "<function ActorCriticPolicy.forward at 0x7f310239c310>",
        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f310239c3a0>",
        "_predict": "<function ActorCriticPolicy._predict at 0x7f310239c430>",
        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f310239c4c0>",
        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f310239c550>",
        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f310239c5e0>",
        "__abstractmethods__": "frozenset()",
        "_abc_impl": "<_abc_data object at 0x7f3102410c90>"
    },
    "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": 3014656,
    "_total_timesteps": 3000000,
    "_num_timesteps_at_start": 0,
    "seed": null,
    "action_noise": null,
    "start_time": 1672103929710167767,
    "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:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAQAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="
    },
    "_last_original_obs": null,
    "_episode_num": 0,
    "use_sde": false,
    "sde_sample_freq": -1,
    "_current_progress_remaining": -0.004885333333333408,
    "ep_info_buffer": {
        ":type:": "<class 'collections.deque'>",
        ":serialized:": "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"
    },
    "ep_success_buffer": {
        ":type:": "<class 'collections.deque'>",
        ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
    },
    "_n_updates": 736,
    "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
}