{
    "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 0x7efb1205e290>",
        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7efb1205e320>",
        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7efb1205e3b0>",
        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7efb1205e440>",
        "_build": "<function ActorCriticPolicy._build at 0x7efb1205e4d0>",
        "forward": "<function ActorCriticPolicy.forward at 0x7efb1205e560>",
        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7efb1205e5f0>",
        "_predict": "<function ActorCriticPolicy._predict at 0x7efb1205e680>",
        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7efb1205e710>",
        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7efb1205e7a0>",
        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7efb1205e830>",
        "__abstractmethods__": "frozenset()",
        "_abc_impl": "<_abc_data object at 0x7efb120ac750>"
    },
    "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": 16384,
    "_total_timesteps": 100,
    "_num_timesteps_at_start": 0,
    "seed": null,
    "action_noise": null,
    "start_time": 1652626913.8750818,
    "learning_rate": 0.0003,
    "tensorboard_log": null,
    "lr_schedule": {
        ":type:": "<class 'function'>",
        ":serialized:": "gAWVvwIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwNX2J1aWx0aW5fdHlwZZSTlIwKTGFtYmRhVHlwZZSFlFKUKGgCjAhDb2RlVHlwZZSFlFKUKEsBSwBLAUsBSxNDBIgAUwCUToWUKYwBX5SFlIxIL3Vzci9sb2NhbC9saWIvcHl0aG9uMy43L2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lIwEZnVuY5RLgEMCAAGUjAN2YWyUhZQpdJRSlH2UKIwLX19wYWNrYWdlX1+UjBhzdGFibGVfYmFzZWxpbmVzMy5jb21tb26UjAhfX25hbWVfX5SMHnN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi51dGlsc5SMCF9fZmlsZV9flIxIL3Vzci9sb2NhbC9saWIvcHl0aG9uMy43L2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaCB9lH2UKGgXaA6MDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgYjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz8zqSowVTJhhZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"
    },
    "_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": -162.84,
    "ep_info_buffer": {
        ":type:": "<class 'collections.deque'>",
        ":serialized:": "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"
    },
    "ep_success_buffer": {
        ":type:": "<class 'collections.deque'>",
        ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
    },
    "_n_updates": 4,
    "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
}