{
    "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 0x7f48257badd0>",
        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f48257bae60>",
        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f48257baef0>",
        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f48257baf80>",
        "_build": "<function ActorCriticPolicy._build at 0x7f48257c0050>",
        "forward": "<function ActorCriticPolicy.forward at 0x7f48257c00e0>",
        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f48257c0170>",
        "_predict": "<function ActorCriticPolicy._predict at 0x7f48257c0200>",
        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f48257c0290>",
        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f48257c0320>",
        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f48257c03b0>",
        "__abstractmethods__": "frozenset()",
        "_abc_impl": "<_abc_data object at 0x7f4825789a20>"
    },
    "verbose": 1,
    "policy_kwargs": {},
    "observation_space": {
        ":type:": "<class 'gym.spaces.box.Box'>",
        ":serialized:": "gAWVngEAAAAAAACMDmd5bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lGgFk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMBXNoYXBllEsIhZSMA2xvd5SMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAAAAAgP8AAID/AACA/wAAgP8AAID/AACA/wAAgP8AAID/lGgKSwiFlIwBQ5R0lFKUjARoaWdolGgSKJYgAAAAAAAAAAAAgH8AAIB/AACAfwAAgH8AAIB/AACAfwAAgH8AAIB/lGgKSwiFlGgVdJRSlIwNYm91bmRlZF9iZWxvd5RoEiiWCAAAAAAAAAAAAAAAAAAAAJRoB4wCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksIhZRoFXSUUpSMDWJvdW5kZWRfYWJvdmWUaBIolggAAAAAAAAAAAAAAAAAAACUaCFLCIWUaBV0lFKUjApfbnBfcmFuZG9tlE51Yi4=",
        "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:": "gAWVgQAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwFc2hhcGWUKYwFZHR5cGWUjAVudW1weZRoB5OUjAJpOJSJiIeUUpQoSwOMATyUTk5OSv////9K/////0sAdJRijApfbnBfcmFuZG9tlE51Yi4=",
        "n": 4,
        "shape": [],
        "dtype": "int64",
        "_np_random": null
    },
    "n_envs": 16,
    "num_timesteps": 507904,
    "_total_timesteps": 500000,
    "_num_timesteps_at_start": 0,
    "seed": null,
    "action_noise": null,
    "start_time": 1652068083.5618973,
    "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": -0.015808000000000044,
    "ep_info_buffer": {
        ":type:": "<class 'collections.deque'>",
        ":serialized:": "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"
    },
    "ep_success_buffer": {
        ":type:": "<class 'collections.deque'>",
        ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
    },
    "_n_updates": 124,
    "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:": "gAWVvwIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwNX2J1aWx0aW5fdHlwZZSTlIwKTGFtYmRhVHlwZZSFlFKUKGgCjAhDb2RlVHlwZZSFlFKUKEsBSwBLAUsBSxNDBIgAUwCUToWUKYwBX5SFlIxIL3Vzci9sb2NhbC9saWIvcHl0aG9uMy43L2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lIwEZnVuY5RLgEMCAAGUjAN2YWyUhZQpdJRSlH2UKIwLX19wYWNrYWdlX1+UjBhzdGFibGVfYmFzZWxpbmVzMy5jb21tb26UjAhfX25hbWVfX5SMHnN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi51dGlsc5SMCF9fZmlsZV9flIxIL3Vzci9sb2NhbC9saWIvcHl0aG9uMy43L2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaCB9lH2UKGgXaA6MDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgYjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz/JmZmZmZmahZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"
    },
    "clip_range_vf": null,
    "normalize_advantage": true,
    "target_kl": null
}