{
    "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 0x7f590a0f5c20>",
        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f590a0f5cb0>",
        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f590a0f5d40>",
        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f590a0f5dd0>",
        "_build": "<function ActorCriticPolicy._build at 0x7f590a0f5e60>",
        "forward": "<function ActorCriticPolicy.forward at 0x7f590a0f5ef0>",
        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f590a0f5f80>",
        "_predict": "<function ActorCriticPolicy._predict at 0x7f590a0fa050>",
        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f590a0fa0e0>",
        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f590a0fa170>",
        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f590a0fa200>",
        "__abstractmethods__": "frozenset()",
        "_abc_impl": "<_abc_data object at 0x7f590a0c3a20>"
    },
    "verbose": 0,
    "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": 1,
    "num_timesteps": 200704,
    "_total_timesteps": 200000,
    "_num_timesteps_at_start": 0,
    "seed": null,
    "action_noise": null,
    "start_time": 1663335142.815542,
    "learning_rate": 0.0003,
    "tensorboard_log": null,
    "lr_schedule": {
        ":type:": "<class 'function'>",
        ":serialized:": "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"
    },
    "_last_obs": {
        ":type:": "<class 'numpy.ndarray'>",
        ":serialized:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAACAcBz5w6ZY+Gs9JPaJQVr6noSk9TjkfPQAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksBSwiGlIwBQ5R0lFKULg=="
    },
    "_last_episode_starts": {
        ":type:": "<class 'numpy.ndarray'>",
        ":serialized:": "gAWVdAAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYBAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwGFlIwBQ5R0lFKULg=="
    },
    "_last_original_obs": null,
    "_episode_num": 0,
    "use_sde": false,
    "sde_sample_freq": -1,
    "_current_progress_remaining": -0.0035199999999999676,
    "ep_info_buffer": {
        ":type:": "<class 'collections.deque'>",
        ":serialized:": "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"
    },
    "ep_success_buffer": {
        ":type:": "<class 'collections.deque'>",
        ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
    },
    "_n_updates": 980,
    "n_steps": 2048,
    "gamma": 0.99,
    "gae_lambda": 0.95,
    "ent_coef": 0.0,
    "vf_coef": 0.5,
    "max_grad_norm": 0.5,
    "batch_size": 64,
    "n_epochs": 10,
    "clip_range": {
        ":type:": "<class 'function'>",
        ":serialized:": "gAWVwQIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsBSwFLE0MEiABTAJROhZQpjAFflIWUjEgvdXNyL2xvY2FsL2xpYi9weXRob24zLjcvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUjARmdW5jlEuAQwIAAZSMA3ZhbJSFlCl0lFKUfZQojAtfX3BhY2thZ2VfX5SMGHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbpSMCF9fbmFtZV9flIwec3RhYmxlX2Jhc2VsaW5lczMuY29tbW9uLnV0aWxzlIwIX19maWxlX1+UjEgvdXNyL2xvY2FsL2xpYi9weXRob24zLjcvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUdU5OaACMEF9tYWtlX2VtcHR5X2NlbGyUk5QpUpSFlHSUUpSMHGNsb3VkcGlja2xlLmNsb3VkcGlja2xlX2Zhc3SUjBJfZnVuY3Rpb25fc2V0c3RhdGWUk5RoH32UfZQoaBZoDYwMX19xdWFsbmFtZV9flIwZY29uc3RhbnRfZm4uPGxvY2Fscz4uZnVuY5SMD19fYW5ub3RhdGlvbnNfX5R9lIwOX19rd2RlZmF1bHRzX1+UTowMX19kZWZhdWx0c19flE6MCl9fbW9kdWxlX1+UaBeMB19fZG9jX1+UTowLX19jbG9zdXJlX1+UaACMCl9tYWtlX2NlbGyUk5RHP8mZmZmZmZqFlFKUhZSMF19jbG91ZHBpY2tsZV9zdWJtb2R1bGVzlF2UjAtfX2dsb2JhbHNfX5R9lHWGlIZSMC4="
    },
    "clip_range_vf": null,
    "normalize_advantage": true,
    "target_kl": null
}