{
    "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 0x78505be40af0>",
        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x78505be40b80>",
        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x78505be40c10>",
        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x78505be40ca0>",
        "_build": "<function ActorCriticPolicy._build at 0x78505be40d30>",
        "forward": "<function ActorCriticPolicy.forward at 0x78505be40dc0>",
        "extract_features": "<function ActorCriticPolicy.extract_features at 0x78505be40e50>",
        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x78505be40ee0>",
        "_predict": "<function ActorCriticPolicy._predict at 0x78505be40f70>",
        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x78505be41000>",
        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x78505be41090>",
        "predict_values": "<function ActorCriticPolicy.predict_values at 0x78505be41120>",
        "__abstractmethods__": "frozenset()",
        "_abc_impl": "<_abc._abc_data object at 0x78505bddf880>"
    },
    "verbose": 1,
    "policy_kwargs": {},
    "num_timesteps": 1015808,
    "_total_timesteps": 1000000,
    "_num_timesteps_at_start": 0,
    "seed": null,
    "action_noise": null,
    "start_time": 1693244156582963289,
    "learning_rate": 0.0003,
    "tensorboard_log": null,
    "_last_obs": {
        ":type:": "<class 'numpy.ndarray'>",
        ":serialized:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAADNcn7yex6g/1cXqvSdT177Aq0K9o13+vQAAAAAAAAAAEDubPldiaD8ItNg+o5UKvzd90D7SIZM9AAAAAAAAAADGeTG+ccFOP9v92D3UsLG+ClOrvEWywDwAAAAAAAAAALP5SD1o0sM+IpA2vOFMZ76QwZU8Zi0PPgAAAAAAAAAAzQS8vUzRqj8mrE++6y6rvtXtGL5IcQq+AAAAAAAAAACzEiA9SNWWuiqgiTOMvlmurqT5um7JrbMAAIA/AACAP4CGsT1cO0a64DfXuO94JjRbubm6Q54AOAAAgD8AAIA/7r+Avjwwqz/+a7G+M5qTvmQbrL5LhFm9AAAAAAAAAAAIHIS+25yAPwByAD1gm8e+VmoGvpbI/D0AAAAAAAAAAJoel7z+veY+yxWwPa9Jnr4rR908I11CPQAAAAAAAAAA2hJivsHQhj92AiS+U0O0vhJMjb4GPNg9AAAAAAAAAAAN0oK9GT4VP81MoD3AhZa+w3REPRjTVLwAAAAAAAAAACAdD75VJ40/drFuvlJ+gL742F++F6UmvAAAAAAAAAAAmmZLPbhD/Lsqxnu8gUIiPQ+pWT0mBwS+AACAPwAAgD+GNw6+88iUPpDk2T2Rl1u+qbAcPAUKU70AAAAAAAAAAIBwRL0DGBe8vwgyPJJ1tjzfxYA9TAyWvQAAgD8AAIA/lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksQSwiGlIwBQ5R0lFKULg=="
    },
    "_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,
    "_stats_window_size": 100,
    "ep_info_buffer": {
        ":type:": "<class 'collections.deque'>",
        ":serialized:": "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"
    },
    "ep_success_buffer": {
        ":type:": "<class 'collections.deque'>",
        ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
    },
    "_n_updates": 248,
    "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,
    "observation_space": {
        ":type:": "<class 'gymnasium.spaces.box.Box'>",
        ":serialized:": "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",
        "dtype": "float32",
        "bounded_below": "[ True  True  True  True  True  True  True  True]",
        "bounded_above": "[ True  True  True  True  True  True  True  True]",
        "_shape": [
            8
        ],
        "low": "[-90.        -90.         -5.         -5.         -3.1415927  -5.\n  -0.         -0.       ]",
        "high": "[90.        90.         5.         5.         3.1415927  5.\n  1.         1.       ]",
        "low_repr": "[-90.        -90.         -5.         -5.         -3.1415927  -5.\n  -0.         -0.       ]",
        "high_repr": "[90.        90.         5.         5.         3.1415927  5.\n  1.         1.       ]",
        "_np_random": null
    },
    "action_space": {
        ":type:": "<class 'gymnasium.spaces.discrete.Discrete'>",
        ":serialized:": "gAWV/QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgLjAJpOJSJiIeUUpQoSwNoD05OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu",
        "n": "4",
        "start": "0",
        "_shape": [],
        "dtype": "int64",
        "_np_random": null
    },
    "n_envs": 16,
    "lr_schedule": {
        ":type:": "<class 'function'>",
        ":serialized:": "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"
    }
}