{
    "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 0x7fe0531baa60>",
        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fe0531baaf0>",
        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fe0531bab80>",
        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fe0531bac10>",
        "_build": "<function ActorCriticPolicy._build at 0x7fe0531baca0>",
        "forward": "<function ActorCriticPolicy.forward at 0x7fe0531bad30>",
        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7fe0531badc0>",
        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fe0531bae50>",
        "_predict": "<function ActorCriticPolicy._predict at 0x7fe0531baee0>",
        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fe0531baf70>",
        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fe0531c3040>",
        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fe0531c30d0>",
        "__abstractmethods__": "frozenset()",
        "_abc_impl": "<_abc._abc_data object at 0x7fe0531bfc80>"
    },
    "verbose": 1,
    "policy_kwargs": {},
    "observation_space": {
        ":type:": "<class 'gym.spaces.box.Box'>",
        ":serialized:": "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",
        "dtype": "float32",
        "_shape": [
            24
        ],
        "low": "[-inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf\n -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf]",
        "high": "[inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf\n inf inf inf inf inf inf]",
        "bounded_below": "[False False False False False False False False False False False False\n False False False False False False False False False False False False]",
        "bounded_above": "[False False False False False False False False False False False False\n False False False False False False False False False False False False]",
        "_np_random": null
    },
    "action_space": {
        ":type:": "<class 'gym.spaces.box.Box'>",
        ":serialized:": "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",
        "dtype": "float32",
        "_shape": [
            4
        ],
        "low": "[-1. -1. -1. -1.]",
        "high": "[1. 1. 1. 1.]",
        "bounded_below": "[ True  True  True  True]",
        "bounded_above": "[ True  True  True  True]",
        "_np_random": null
    },
    "n_envs": 16,
    "num_timesteps": 507904,
    "_total_timesteps": 500000,
    "_num_timesteps_at_start": 0,
    "seed": null,
    "action_noise": null,
    "start_time": 1677409837183350018,
    "learning_rate": 0.0003,
    "tensorboard_log": null,
    "lr_schedule": {
        ":type:": "<class 'function'>",
        ":serialized:": "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"
    },
    "_last_obs": null,
    "_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,
    "ep_info_buffer": {
        ":type:": "<class 'collections.deque'>",
        ":serialized:": "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"
    },
    "ep_success_buffer": {
        ":type:": "<class 'collections.deque'>",
        ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
    },
    "_n_updates": 212,
    "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": 256,
    "n_epochs": 4,
    "clip_range": {
        ":type:": "<class 'function'>",
        ":serialized:": "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"
    },
    "clip_range_vf": null,
    "normalize_advantage": true,
    "target_kl": null
}