{
    "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 0x7f695c6f5160>",
        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f695c6f51f0>",
        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f695c6f5280>",
        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f695c6f5310>",
        "_build": "<function ActorCriticPolicy._build at 0x7f695c6f53a0>",
        "forward": "<function ActorCriticPolicy.forward at 0x7f695c6f5430>",
        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f695c6f54c0>",
        "_predict": "<function ActorCriticPolicy._predict at 0x7f695c6f5550>",
        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f695c6f55e0>",
        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f695c6f5670>",
        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f695c6f5700>",
        "__abstractmethods__": "frozenset()",
        "_abc_impl": "<_abc._abc_data object at 0x7f695c6f3a80>"
    },
    "verbose": 0,
    "policy_kwargs": {},
    "observation_space": {
        ":type:": "<class 'gym.spaces.box.Box'>",
        ":serialized:": "gAWVnwEAAAAAAACMDmd5bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lGgFk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMBl9zaGFwZZRLCIWUjANsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWIAAAAAAAAAAAAID/AACA/wAAgP8AAID/AACA/wAAgP8AAID/AACA/5RoCksIhZSMAUOUdJRSlIwEaGlnaJRoEiiWIAAAAAAAAAAAAIB/AACAfwAAgH8AAIB/AACAfwAAgH8AAIB/AACAf5RoCksIhZRoFXSUUpSMDWJvdW5kZWRfYmVsb3eUaBIolggAAAAAAAAAAAAAAAAAAACUaAeMAmIxlImIh5RSlChLA4wBfJROTk5K/////0r/////SwB0lGJLCIWUaBV0lFKUjA1ib3VuZGVkX2Fib3ZllGgSKJYIAAAAAAAAAAAAAAAAAAAAlGghSwiFlGgVdJRSlIwKX25wX3JhbmRvbZROdWIu",
        "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:": "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",
        "n": 4,
        "_shape": [],
        "dtype": "int64",
        "_np_random": "RandomState(MT19937)"
    },
    "n_envs": 16,
    "num_timesteps": 15007744,
    "_total_timesteps": 15000000.0,
    "_num_timesteps_at_start": 0,
    "seed": null,
    "action_noise": null,
    "start_time": 1671039213424963915,
    "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": -0.0005162666666667093,
    "ep_info_buffer": {
        ":type:": "<class 'collections.deque'>",
        ":serialized:": "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"
    },
    "ep_success_buffer": {
        ":type:": "<class 'collections.deque'>",
        ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
    },
    "_n_updates": 3664,
    "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
}