{
    "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 0x7fde949088b0>",
        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fde94908940>",
        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fde949089d0>",
        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fde94908a60>",
        "_build": "<function ActorCriticPolicy._build at 0x7fde94908af0>",
        "forward": "<function ActorCriticPolicy.forward at 0x7fde94908b80>",
        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fde94908c10>",
        "_predict": "<function ActorCriticPolicy._predict at 0x7fde94908ca0>",
        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fde94908d30>",
        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fde94908dc0>",
        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fde94908e50>",
        "__abstractmethods__": "frozenset()",
        "_abc_impl": "<_abc_data object at 0x7fde948fcf90>"
    },
    "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": 1015808,
    "_total_timesteps": 1000000,
    "_num_timesteps_at_start": 0,
    "seed": null,
    "action_noise": null,
    "start_time": 1670347093052903014,
    "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:": "gAWVdRAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIaccNv5vqOkCUhpRSlIwBbJRLxowBdJRHQJvhfLvCuU51fZQoaAZoCWgPQwjRQCybef9yQJSGlFKUaBVNxQFoFkdAm+MoIfKZD3V9lChoBmgJaA9DCMWp1sIs9HFAlIaUUpRoFU0JAWgWR0Cb5BSSvC/HdX2UKGgGaAloD0MI+GuyRj1eYUCUhpRSlGgVTegDaBZHQJvlPJFLFn91fZQoaAZoCWgPQwjfGW1VEvdvQJSGlFKUaBVNJgNoFkdAm+VyOBDohnV9lChoBmgJaA9DCFG8ytomqmRAlIaUUpRoFU3oA2gWR0Cb5oBEroW6dX2UKGgGaAloD0MIQpdw6C3lcECUhpRSlGgVTYACaBZHQJvo4q/dqL11fZQoaAZoCWgPQwj3dktywIhVQJSGlFKUaBVN6ANoFkdAm+mFiz9jw3V9lChoBmgJaA9DCG7fo/46RHBAlIaUUpRoFU3cAmgWR0Cb6zvlU6xPdX2UKGgGaAloD0MIBK4rZgS/bUCUhpRSlGgVTS4BaBZHQJwGCO0b9611fZQoaAZoCWgPQwi1GhL32N5jQJSGlFKUaBVN6ANoFkdAnAbCeI2wV3V9lChoBmgJaA9DCMg/M4jPRXBAlIaUUpRoFU2VAmgWR0CcCOf1HvtudX2UKGgGaAloD0MIaEEo76M9ckCUhpRSlGgVTf4BaBZHQJwKj4wh4dJ1fZQoaAZoCWgPQwhz1xLyQbdvQJSGlFKUaBVN4AFoFkdAnAq9qYZ2p3V9lChoBmgJaA9DCHhGW5XE5WZAlIaUUpRoFU3oA2gWR0CcDFOMVDa5dX2UKGgGaAloD0MIn5PeNz7JYECUhpRSlGgVTegDaBZHQJwNBa6jFhp1fZQoaAZoCWgPQwjKwtfXup5uQJSGlFKUaBVN8gFoFkdAnA1yFsYVI3V9lChoBmgJaA9DCExQw7fwU3FAlIaUUpRoFU06A2gWR0CcDXvlU6xPdX2UKGgGaAloD0MIkbqdfWXyY0CUhpRSlGgVTegDaBZHQJwO70nPVut1fZQoaAZoCWgPQwgqqn6lcztyQJSGlFKUaBVN5wJoFkdAnBFFa4c3l3V9lChoBmgJaA9DCOG2tvD8vHBAlIaUUpRoFU0jAWgWR0CcEhHGCI1tdX2UKGgGaAloD0MIlUc3wiJTcUCUhpRSlGgVTaACaBZHQJwSSHWSU1R1fZQoaAZoCWgPQwijsfZ3tu9sQJSGlFKUaBVNdgJoFkdAnBXQ9FF2FHV9lChoBmgJaA9DCB8vpMNDG3BAlIaUUpRoFU1mAmgWR0CcFxO/tY0VdX2UKGgGaAloD0MIZoaNsn4EUkCUhpRSlGgVS99oFkdAnBu/mYBvJnV9lChoBmgJaA9DCPEvgsbMKW1AlIaUUpRoFU2ZAWgWR0CcHGx9XtBwdX2UKGgGaAloD0MIKc3mcRj8bECUhpRSlGgVTTEBaBZHQJwfeBqbjLl1fZQoaAZoCWgPQwjyJVRwOKlyQJSGlFKUaBVNyAFoFkdAnB+c7lq8DnV9lChoBmgJaA9DCGxB740hf29AlIaUUpRoFU0PAmgWR0CcIEZQpF1CdX2UKGgGaAloD0MID313K8u7aECUhpRSlGgVTegDaBZHQJwh/YlIEr51fZQoaAZoCWgPQwgvhnKiXRVxQJSGlFKUaBVN2ANoFkdAnCVW5lOGkHV9lChoBmgJaA9DCH3ogvqWt2lAlIaUUpRoFU21AWgWR0CcLBcoH9m6dX2UKGgGaAloD0MIqIsUysJ8cUCUhpRSlGgVTVQBaBZHQJws2+xnnMd1fZQoaAZoCWgPQwiISbiQR/NtQJSGlFKUaBVN9gFoFkdAnC2/TkQwsXV9lChoBmgJaA9DCLND/MPWQXFAlIaUUpRoFU3xAmgWR0CcLnntv4ucdX2UKGgGaAloD0MI58OzBNlhcUCUhpRSlGgVTS4BaBZHQJwuwRaouPF1fZQoaAZoCWgPQwjexmZH6nxxQJSGlFKUaBVNCwNoFkdAnC+JiqhlDnV9lChoBmgJaA9DCLt868N6GGxAlIaUUpRoFU0MA2gWR0CcRHX7tRekdX2UKGgGaAloD0MItmeWBKjLZUCUhpRSlGgVTegDaBZHQJxEqAmReTp1fZQoaAZoCWgPQwhh4/p3/a5yQJSGlFKUaBVNYgFoFkdAnEVu58Sf2HV9lChoBmgJaA9DCPQ1y2Uj+2RAlIaUUpRoFU3oA2gWR0CcRtTzND+jdX2UKGgGaAloD0MIx4FXy11ZckCUhpRSlGgVTdoBaBZHQJxHyDYh+v11fZQoaAZoCWgPQwhuNIC3gPdwQJSGlFKUaBVN3wNoFkdAnEfGP5pJw3V9lChoBmgJaA9DCOUrgZTY8G5AlIaUUpRoFU04AmgWR0CcSEunMt9QdX2UKGgGaAloD0MIC5jArbuBLECUhpRSlGgVS+JoFkdAnEzv/echDHV9lChoBmgJaA9DCH/4+e/Btm1AlIaUUpRoFU0OAWgWR0CcTsGX5WRzdX2UKGgGaAloD0MIqg65Ge6vYUCUhpRSlGgVTegDaBZHQJxPp9RaX8h1fZQoaAZoCWgPQwjIYMWpFu9xQJSGlFKUaBVNwgFoFkdAnFGGXHBDX3V9lChoBmgJaA9DCGcqxCPxEXJAlIaUUpRoFU2dAWgWR0CcUhn1WbPQdX2UKGgGaAloD0MIVhFuMqrhcECUhpRSlGgVTVEBaBZHQJxTA5wOvuB1fZQoaAZoCWgPQwiI2GDhZFRyQJSGlFKUaBVNXwJoFkdAnFpLSVnmJXV9lChoBmgJaA9DCGiVmdJ6Zm1AlIaUUpRoFU05AmgWR0CcWm+eOGTLdX2UKGgGaAloD0MI1Em2upzKRECUhpRSlGgVS85oFkdAnFuN5dGAkXV9lChoBmgJaA9DCDkqN1HL/GZAlIaUUpRoFU3oA2gWR0CcXrbLEDQrdX2UKGgGaAloD0MII74Tsx7VcECUhpRSlGgVTY4BaBZHQJxiGcH4XXR1fZQoaAZoCWgPQwilZ3qJMQlxQJSGlFKUaBVNDwNoFkdAnGOBkmQbM3V9lChoBmgJaA9DCNEgBU8h0U5AlIaUUpRoFUvYaBZHQJxkZTQ3PzF1fZQoaAZoCWgPQwhgVijSfc1hQJSGlFKUaBVN6ANoFkdAnGTOgg5imXV9lChoBmgJaA9DCOeKUkLwVXFAlIaUUpRoFU0NAmgWR0CcZSdH2AXmdX2UKGgGaAloD0MIgq59AT1obkCUhpRSlGgVTawBaBZHQJxlMlv60pp1fZQoaAZoCWgPQwiymxn9KPZwQJSGlFKUaBVNnQJoFkdAnGXmZqmCRXV9lChoBmgJaA9DCFIpdjTOB3JAlIaUUpRoFU0QAmgWR0CcafXYUWVNdX2UKGgGaAloD0MIfJv+7EeBZUCUhpRSlGgVTegDaBZHQJxqEYaYNRZ1fZQoaAZoCWgPQwjQRUPGoxtwQJSGlFKUaBVNKQFoFkdAnGrEupS75HV9lChoBmgJaA9DCNJRDmYTol9AlIaUUpRoFU3oA2gWR0Ccg74mTkhidX2UKGgGaAloD0MIKSMuAE10ckCUhpRSlGgVTTABaBZHQJyEdl05lvt1fZQoaAZoCWgPQwjBNuLJbvlxQJSGlFKUaBVNNQJoFkdAnISb0jC53HV9lChoBmgJaA9DCJJbk25L+2NAlIaUUpRoFU3oA2gWR0CchPQb+98JdX2UKGgGaAloD0MIpHGo3wWlZkCUhpRSlGgVTegDaBZHQJyE8ngHeJp1fZQoaAZoCWgPQwjSj4ZTJrZyQJSGlFKUaBVNggFoFkdAnIVeaBqbjXV9lChoBmgJaA9DCFsomZzaBnBAlIaUUpRoFUv+aBZHQJyG4ffXPJJ1fZQoaAZoCWgPQwjysbtASfxtQJSGlFKUaBVNVwJoFkdAnIbxV6u4gHV9lChoBmgJaA9DCBNm2v7VonBAlIaUUpRoFU3PAWgWR0CciMx2B8QadX2UKGgGaAloD0MIPL1SluH/cUCUhpRSlGgVTTcCaBZHQJyKtl7MPjJ1fZQoaAZoCWgPQwgwmwDDcuFmQJSGlFKUaBVN6ANoFkdAnItSHZbpvHV9lChoBmgJaA9DCJliDoJOInJAlIaUUpRoFU0vAmgWR0CcjRki2UjcdX2UKGgGaAloD0MI2BGHbKA5c0CUhpRSlGgVTVUCaBZHQJyOTvG6wt91fZQoaAZoCWgPQwjcSUT4F09BQJSGlFKUaBVLz2gWR0CcjppIMBp6dX2UKGgGaAloD0MIUFCKVq4hcUCUhpRSlGgVTWECaBZHQJyPJW+49X91fZQoaAZoCWgPQwiyLQPOEglxQJSGlFKUaBVNMwFoFkdAnJAXRCx/u3V9lChoBmgJaA9DCK+T+rK0OlVAlIaUUpRoFUveaBZHQJyROxW1c+t1fZQoaAZoCWgPQwh6xyk6kh5uQJSGlFKUaBVNagFoFkdAnJFipFTef3V9lChoBmgJaA9DCES+S6nL325AlIaUUpRoFU1WAWgWR0Cck6w5NoJzdX2UKGgGaAloD0MIT8sPXOUfbkCUhpRSlGgVTScBaBZHQJyWAQ+UyHp1fZQoaAZoCWgPQwhUUiegyWFwQJSGlFKUaBVNrAJoFkdAnJcl4Pf8/HV9lChoBmgJaA9DCO87hsc+7XFAlIaUUpRoFU2kAmgWR0Ccl45jpcHGdX2UKGgGaAloD0MIn8cozzwjcECUhpRSlGgVTfEBaBZHQJyXlD8cdYJ1fZQoaAZoCWgPQwjPaRZo97pyQJSGlFKUaBVN7wFoFkdAnJfkJrtVrHV9lChoBmgJaA9DCPFG5pH/K3BAlIaUUpRoFU1NAWgWR0CcmZNvwVj7dX2UKGgGaAloD0MIp11MM52ncUCUhpRSlGgVTUgBaBZHQJyayW+oLoh1fZQoaAZoCWgPQwimZDkJpYlJQJSGlFKUaBVLxmgWR0CcmwKWLP2PdX2UKGgGaAloD0MI9BYP7zkGckCUhpRSlGgVTbUBaBZHQJybtezD4xl1fZQoaAZoCWgPQwhEa0WbYxpxQJSGlFKUaBVNcgJoFkdAnJwVdLQHA3V9lChoBmgJaA9DCII8u3zrN0VAlIaUUpRoFUvaaBZHQJyfGkO7QLN1fZQoaAZoCWgPQwirz9VW7O/8P5SGlFKUaBVL0WgWR0CcnyKF7D2rdX2UKGgGaAloD0MIsvM2NjvqbkCUhpRSlGgVTYIBaBZHQJyfUwGnn+11fZQoaAZoCWgPQwj8cfvlE2ZwQJSGlFKUaBVNIQFoFkdAnKATjJdSl3V9lChoBmgJaA9DCHJvfsNEfUZAlIaUUpRoFUvGaBZHQJyiSkj5bhZ1fZQoaAZoCWgPQwiAZhAfmKlyQJSGlFKUaBVNjQFoFkdAnKVglOXVsnV9lChoBmgJaA9DCIc0KnCyIXNAlIaUUpRoFU02AWgWR0CcpnjKgZjydWUu"
    },
    "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
}