{
    "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 0x7f4de25914d0>",
        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f4de2591560>",
        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f4de25915f0>",
        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f4de2591680>",
        "_build": "<function ActorCriticPolicy._build at 0x7f4de2591710>",
        "forward": "<function ActorCriticPolicy.forward at 0x7f4de25917a0>",
        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f4de2591830>",
        "_predict": "<function ActorCriticPolicy._predict at 0x7f4de25918c0>",
        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f4de2591950>",
        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f4de25919e0>",
        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f4de2591a70>",
        "__abstractmethods__": "frozenset()",
        "_abc_impl": "<_abc_data object at 0x7f4de25daa20>"
    },
    "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": 1310720,
    "_total_timesteps": 1300000,
    "_num_timesteps_at_start": 0,
    "seed": null,
    "action_noise": null,
    "start_time": 1663511428.543014,
    "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": -0.008246153846153792,
    "ep_info_buffer": {
        ":type:": "<class 'collections.deque'>",
        ":serialized:": "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"
    },
    "ep_success_buffer": {
        ":type:": "<class 'collections.deque'>",
        ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
    },
    "_n_updates": 720,
    "n_steps": 1024,
    "gamma": 0.999269,
    "gae_lambda": 0.98,
    "ent_coef": 0.01,
    "vf_coef": 0.5,
    "max_grad_norm": 0.5,
    "batch_size": 64,
    "n_epochs": 9,
    "clip_range": {
        ":type:": "<class 'function'>",
        ":serialized:": "gAWVwQIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsBSwFLE0MEiABTAJROhZQpjAFflIWUjEgvdXNyL2xvY2FsL2xpYi9weXRob24zLjcvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUjARmdW5jlEuAQwIAAZSMA3ZhbJSFlCl0lFKUfZQojAtfX3BhY2thZ2VfX5SMGHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbpSMCF9fbmFtZV9flIwec3RhYmxlX2Jhc2VsaW5lczMuY29tbW9uLnV0aWxzlIwIX19maWxlX1+UjEgvdXNyL2xvY2FsL2xpYi9weXRob24zLjcvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUdU5OaACMEF9tYWtlX2VtcHR5X2NlbGyUk5QpUpSFlHSUUpSMHGNsb3VkcGlja2xlLmNsb3VkcGlja2xlX2Zhc3SUjBJfZnVuY3Rpb25fc2V0c3RhdGWUk5RoH32UfZQoaBZoDYwMX19xdWFsbmFtZV9flIwZY29uc3RhbnRfZm4uPGxvY2Fscz4uZnVuY5SMD19fYW5ub3RhdGlvbnNfX5R9lIwOX19rd2RlZmF1bHRzX1+UTowMX19kZWZhdWx0c19flE6MCl9fbW9kdWxlX1+UaBeMB19fZG9jX1+UTowLX19jbG9zdXJlX1+UaACMCl9tYWtlX2NlbGyUk5RHP8mZmZmZmZqFlFKUhZSMF19jbG91ZHBpY2tsZV9zdWJtb2R1bGVzlF2UjAtfX2dsb2JhbHNfX5R9lHWGlIZSMC4="
    },
    "clip_range_vf": null,
    "normalize_advantage": true,
    "target_kl": null
}