{
    "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 0x7f1a124f8ef0>",
        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f1a124f8f80>",
        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f1a12501050>",
        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f1a125010e0>",
        "_build": "<function ActorCriticPolicy._build at 0x7f1a12501170>",
        "forward": "<function ActorCriticPolicy.forward at 0x7f1a12501200>",
        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f1a12501290>",
        "_predict": "<function ActorCriticPolicy._predict at 0x7f1a12501320>",
        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f1a125013b0>",
        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f1a12501440>",
        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f1a125014d0>",
        "__abstractmethods__": "frozenset()",
        "_abc_impl": "<_abc_data object at 0x7f1a1254c810>"
    },
    "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": 507904,
    "_total_timesteps": 500000,
    "_num_timesteps_at_start": 0,
    "seed": null,
    "action_noise": null,
    "start_time": 1652214992.403761,
    "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:": "gAWVVxAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIUWovoq22cECUhpRSlIwBbJRL7IwBdJRHQJfeRuUD+zd1fZQoaAZoCWgPQwjkZyPXTaJxQJSGlFKUaBVNAAFoFkdAl95fGEPDpHV9lChoBmgJaA9DCPsHkQy56G9AlIaUUpRoFU0MAWgWR0CX3mr/KhcrdX2UKGgGaAloD0MIYFYo0r01cUCUhpRSlGgVS/5oFkdAl96udCmdiHV9lChoBmgJaA9DCPIIbqRsdHFAlIaUUpRoFU0sAWgWR0CX3qypJf6XdX2UKGgGaAloD0MI+yKhLSebcECUhpRSlGgVS/NoFkdAl9+Y8U21lXV9lChoBmgJaA9DCI3Qz9RrBnJAlIaUUpRoFU0cAWgWR0CX35jy4FzNdX2UKGgGaAloD0MItRfRdgxrcUCUhpRSlGgVTRABaBZHQJffsVKwpvx1fZQoaAZoCWgPQwgb9ntiHbVsQJSGlFKUaBVL9mgWR0CX3+qOtGNJdX2UKGgGaAloD0MI4STNHxPVcECUhpRSlGgVTQ8BaBZHQJfiPujRD1J1fZQoaAZoCWgPQwiyvKsesK1yQJSGlFKUaBVL5GgWR0CX4lWepXIVdX2UKGgGaAloD0MIZDvfT40IckCUhpRSlGgVS+toFkdAl+LmqkuYhXV9lChoBmgJaA9DCHXnieds/3BAlIaUUpRoFUvoaBZHQJfjiouPFNt1fZQoaAZoCWgPQwg/OnXlc9FxQJSGlFKUaBVL7WgWR0CX47yWAwwkdX2UKGgGaAloD0MI626e6hBccUCUhpRSlGgVS+1oFkdAl+PENrj5sXV9lChoBmgJaA9DCHdJnBURxXFAlIaUUpRoFU0CAWgWR0CX49yDqW1MdX2UKGgGaAloD0MIrKqX32mCTkCUhpRSlGgVS8RoFkdAl+Rxu4wyqXV9lChoBmgJaA9DCFHbhlFQw3NAlIaUUpRoFUv4aBZHQJfknbQC0Wx1fZQoaAZoCWgPQwij5UAPNVhyQJSGlFKUaBVNEQFoFkdAl+TxUJfICHV9lChoBmgJaA9DCIi5pGq7CXFAlIaUUpRoFU0GAWgWR0CX5QLHdXT3dX2UKGgGaAloD0MImKQyxRyJbkCUhpRSlGgVTScBaBZHQJflZZJTVDt1fZQoaAZoCWgPQwgUev1JPDpwQJSGlFKUaBVNBQFoFkdAl+YruIAOrnV9lChoBmgJaA9DCL8NMV7zXG1AlIaUUpRoFU0JAWgWR0CX5pA6uGKydX2UKGgGaAloD0MINgGG5Y81cUCUhpRSlGgVTR4BaBZHQJfmq7btZ3d1fZQoaAZoCWgPQwh1PjxLEMNvQJSGlFKUaBVNBQFoFkdAl+kSYw7DEXV9lChoBmgJaA9DCGPVIMxtY29AlIaUUpRoFU0LAWgWR0CX6Skn1FpgdX2UKGgGaAloD0MIi90+qwxrcECUhpRSlGgVTQIBaBZHQJfpjbZezD51fZQoaAZoCWgPQwg6AyMvqw9xQJSGlFKUaBVL6WgWR0CX6bfGdZq3dX2UKGgGaAloD0MIFeEmo8o5b0CUhpRSlGgVS/doFkdAl+ovwRXfZXV9lChoBmgJaA9DCEzhQbOrA3JAlIaUUpRoFU0LAWgWR0CX6mn7HhjwdX2UKGgGaAloD0MICydp/hhucUCUhpRSlGgVTRUBaBZHQJfq3DMvAXV1fZQoaAZoCWgPQwjTwfo/B6JvQJSGlFKUaBVNAAFoFkdAl+sJMYdhiXV9lChoBmgJaA9DCGGkF7W7m3BAlIaUUpRoFUvzaBZHQJfrNfJFLFp1fZQoaAZoCWgPQwgx73GmicJyQJSGlFKUaBVNBgFoFkdAl+tVYU34sXV9lChoBmgJaA9DCD4FwHjGQ3FAlIaUUpRoFUvtaBZHQJfrbbItDlZ1fZQoaAZoCWgPQwgB+n3/JhRyQJSGlFKUaBVNBgFoFkdAl+uTRlYlp3V9lChoBmgJaA9DCPRSsTGvOWxAlIaUUpRoFU0FAWgWR0CX7LCuloDgdX2UKGgGaAloD0MI3sZmR+oqc0CUhpRSlGgVS/NoFkdAl+y+pbUwz3V9lChoBmgJaA9DCDXPEfluNHBAlIaUUpRoFU0cAWgWR0CX7aO5avA5dX2UKGgGaAloD0MI8u7IWC0YcECUhpRSlGgVS/ZoFkdAl+9Ez9CNTHV9lChoBmgJaA9DCHzRHi+k43BAlIaUUpRoFUvuaBZHQJfvi7K7qY91fZQoaAZoCWgPQwgUlnhAWRJwQJSGlFKUaBVNDQFoFkdAl/Czurp7kXV9lChoBmgJaA9DCIRlbOjmoXBAlIaUUpRoFUv6aBZHQJfw7ixVyWB1fZQoaAZoCWgPQwhTWRR20bNwQJSGlFKUaBVL7WgWR0CYAt0fHPu5dX2UKGgGaAloD0MIq+gPzXy+cUCUhpRSlGgVTQ4BaBZHQJgC5ccENfB1fZQoaAZoCWgPQwiEvB5MCp5wQJSGlFKUaBVL+GgWR0CYAv+RYA80dX2UKGgGaAloD0MIwY7/AoGFckCUhpRSlGgVS/RoFkdAmAOMTakAP3V9lChoBmgJaA9DCILjMm4qIHFAlIaUUpRoFU0MAWgWR0CYA/DGtITXdX2UKGgGaAloD0MIpKmezP/6cECUhpRSlGgVTQMBaBZHQJgEJLkCFK11fZQoaAZoCWgPQwhzEd+JmWRwQJSGlFKUaBVNKgFoFkdAmATbKq4pdHV9lChoBmgJaA9DCPgXQWMmZHBAlIaUUpRoFUvxaBZHQJgE/Rv3rUt1fZQoaAZoCWgPQwiIZMix9TtxQJSGlFKUaBVNBQFoFkdAmAaqOPvKEHV9lChoBmgJaA9DCGX/PA2YD3BAlIaUUpRoFU02AWgWR0CYBwzJIUaidX2UKGgGaAloD0MI/MitSbcuckCUhpRSlGgVTQYBaBZHQJgIkdZJTVF1fZQoaAZoCWgPQwj7eVORihtwQJSGlFKUaBVL8WgWR0CYCXHpbD/EdX2UKGgGaAloD0MIu9IyUq+zcECUhpRSlGgVS+ZoFkdAmAm9a2WpqHV9lChoBmgJaA9DCNrKS/7nxXBAlIaUUpRoFUv0aBZHQJgKLrhR64V1fZQoaAZoCWgPQwhz9WOTvB9yQJSGlFKUaBVNAwFoFkdAmApTdtVJc3V9lChoBmgJaA9DCElnYOTljmBAlIaUUpRoFU3oA2gWR0CYCnvGp++edX2UKGgGaAloD0MILskBuxr6bkCUhpRSlGgVS/doFkdAmAsD7l7tzHV9lChoBmgJaA9DCDKTqBe8cXJAlIaUUpRoFU1cAWgWR0CYC7BOpKjBdX2UKGgGaAloD0MICI7LuClyckCUhpRSlGgVTQcBaBZHQJgL6l0o0AN1fZQoaAZoCWgPQwiwx0RKM6RxQJSGlFKUaBVNGQFoFkdAmAyhmTTvzHV9lChoBmgJaA9DCEllijnIonFAlIaUUpRoFU0KAWgWR0CYDP9aEBbOdX2UKGgGaAloD0MIhC12+6z/ckCUhpRSlGgVTTsBaBZHQJgOootthux1fZQoaAZoCWgPQwgF+dnI9UpyQJSGlFKUaBVNHAFoFkdAmBARAGB4EHV9lChoBmgJaA9DCERQNXq1aW5AlIaUUpRoFUvsaBZHQJgQ9wyZa3Z1fZQoaAZoCWgPQwh6F+/HbXtzQJSGlFKUaBVNUAFoFkdAmBF500WM0nV9lChoBmgJaA9DCNifxOcOB3NAlIaUUpRoFUv+aBZHQJgR8KeCkGl1fZQoaAZoCWgPQwiv7e2W5HBvQJSGlFKUaBVL+GgWR0CYEjF4cFQmdX2UKGgGaAloD0MIAizy6wdOb0CUhpRSlGgVS/xoFkdAmBJ6PCEYfnV9lChoBmgJaA9DCJBq2O+JAnBAlIaUUpRoFUv/aBZHQJgSv+m3vx91fZQoaAZoCWgPQwhjKZKvBMZwQJSGlFKUaBVNAAFoFkdAmBQm07bL2nV9lChoBmgJaA9DCFAZ/z4jhHFAlIaUUpRoFU0aAWgWR0CYFEi0fHPvdX2UKGgGaAloD0MIY9NKIRBockCUhpRSlGgVTQABaBZHQJgUa9g4Otp1fZQoaAZoCWgPQwiAme/gJ0BxQJSGlFKUaBVNAwFoFkdAmBVUv9LpR3V9lChoBmgJaA9DCHtpigAn2mxAlIaUUpRoFUv2aBZHQJgVVdQfp2V1fZQoaAZoCWgPQwhD/plBfGluQJSGlFKUaBVL/2gWR0CYF1qioKlYdX2UKGgGaAloD0MIIm5OJQOgUUCUhpRSlGgVS7RoFkdAmBfv5+H8CXV9lChoBmgJaA9DCFWgFoMHIWRAlIaUUpRoFU3oA2gWR0CYGO9Zid8RdX2UKGgGaAloD0MIPQytTs7RckCUhpRSlGgVTQYBaBZHQJgZBinYQJ51fZQoaAZoCWgPQwhR9wFI7ThwQJSGlFKUaBVNDQFoFkdAmBobzXjEN3V9lChoBmgJaA9DCAe0dAWbTXJAlIaUUpRoFUvuaBZHQJgatqSHM2Z1fZQoaAZoCWgPQwjohTsXhityQJSGlFKUaBVNEgFoFkdAmBrAGOdXk3V9lChoBmgJaA9DCCtOtRamLXFAlIaUUpRoFU0FAWgWR0CYGzQ5myxBdX2UKGgGaAloD0MIdck4RnIHcECUhpRSlGgVTRQBaBZHQJgba0lZ5iV1fZQoaAZoCWgPQwgmUS/49NJyQJSGlFKUaBVL+2gWR0CYHHHWSU1RdX2UKGgGaAloD0MIJnFWRM1rbkCUhpRSlGgVS/doFkdAmBxva6BiC3V9lChoBmgJaA9DCILjMm6qr3BAlIaUUpRoFUvvaBZHQJgdLNVzZHx1fZQoaAZoCWgPQwhsX0AvXHByQJSGlFKUaBVNCwFoFkdAmB0qnm7rcHV9lChoBmgJaA9DCIAnLVzWyXBAlIaUUpRoFU0bAWgWR0CYHpBrvb48dX2UKGgGaAloD0MIm1jgK7rjcECUhpRSlGgVS/ZoFkdAmB9naN+9anV9lChoBmgJaA9DCKcFL/pKHHJAlIaUUpRoFU0bAWgWR0CYIWOmzjWDdX2UKGgGaAloD0MIXOhKBKr/ckCUhpRSlGgVTQcBaBZHQJghug13t8h1fZQoaAZoCWgPQwhB9KRM6nZuQJSGlFKUaBVNFgFoFkdAmCJjslb/wXV9lChoBmgJaA9DCFRXPstzH21AlIaUUpRoFU0BAWgWR0CYIstf5ULldX2UKGgGaAloD0MIsHWpEfowcUCUhpRSlGgVS/toFkdAmCM2dNFjNXV9lChoBmgJaA9DCDDXogXoU29AlIaUUpRoFUvxaBZHQJgjYhNdqtZ1fZQoaAZoCWgPQwi7Jw8Ldb5wQJSGlFKUaBVNAAFoFkdAmCNrhvR7Z3V9lChoBmgJaA9DCHWPbK6aCF9AlIaUUpRoFU3oA2gWR0CYI3V0Lc9GdWUu"
    },
    "ep_success_buffer": {
        ":type:": "<class 'collections.deque'>",
        ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
    },
    "_n_updates": 372,
    "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
}