config.json

{"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 0x7f58d5135cf0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f58d5135d80>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f58d5135e10>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f58d5135ea0>", "_build": "<function ActorCriticPolicy._build at 0x7f58d5135f30>", "forward": "<function ActorCriticPolicy.forward at 0x7f58d5135fc0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f58d5136050>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f58d51360e0>", "_predict": "<function ActorCriticPolicy._predict at 0x7f58d5136170>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f58d5136200>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f58d5136290>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f58d5136320>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f58d51444c0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1682646586931991688, "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, "_stats_window_size": 100, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVgRAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIG0rthRwc8UCUhpRSlIwBbJRN6AOMAXSUR0CifvY3Ns3ydX2UKGgGaAloD0MIP/1nzV3G6kCUhpRSlGgVTegDaBZHQKJ+8EEkjX51fZQoaAZoCWgPQwiOdXGb963yQJSGlFKUaBVN6ANoFkdAon7qujh1knV9lChoBmgJaA9DCKPlQE+gXfJAlIaUUpRoFU3oA2gWR0CifuSBK+SKdX2UKGgGaAloD0MI0y8Rb7ff6kCUhpRSlGgVTegDaBZHQKLQ6cvugHx1fZQoaAZoCWgPQwirl9/p/13oQJSGlFKUaBVN6ANoFkdAotDgoRZlnXV9lChoBmgJaA9DCHAk0KBjt/JAlIaUUpRoFU3oA2gWR0Ci0Nos7MgVdX2UKGgGaAloD0MIwVd060AZ7UCUhpRSlGgVTegDaBZHQKLQ0/h2nsN1fZQoaAZoCWgPQwhZFHaRs63yQJSGlFKUaBVN6ANoFkdAotDN+iJwbXV9lChoBmgJaA9DCEZ+/RDIY/BAlIaUUpRoFU3oA2gWR0Ci0MfYJ3PidX2UKGgGaAloD0MIKxVUVI7e7UCUhpRSlGgVTegDaBZHQKLQwYKpkwx1fZQoaAZoCWgPQwhruMg9o/TvQJSGlFKUaBVN6ANoFkdAotC7yUcGT3V9lChoBmgJaA9DCKZjzjNxVe9AlIaUUpRoFU3oA2gWR0Ci0LW2w3YMdX2UKGgGaAloD0MIOPWBJBVf8UCUhpRSlGgVTegDaBZHQKLQsB5HEuR1fZQoaAZoCWgPQwhMpgrGNsXvQJSGlFKUaBVN6ANoFkdAotARNmDlHXV9lChoBmgJaA9DCC/ej1tG7PFAlIaUUpRoFU3oA2gWR0Ci0Aoc7yQQdX2UKGgGaAloD0MI5WN3gcs580CUhpRSlGgVTegDaBZHQKLQA+WWyC51fZQoaAZoCWgPQwiSrS7nRa3wQJSGlFKUaBVN6ANoFkdAos/9cv/R3XV9lChoBmgJaA9DCAby7DKMFfBAlIaUUpRoFU3oA2gWR0Ciz/efqX4TdX2UKGgGaAloD0MIM95W+gCO9UCUhpRSlGgVTegDaBZHQKLP8Ui6g/V1fZQoaAZoCWgPQwjaVN0jAobvQJSGlFKUaBVN6ANoFkdAovJ8tI0653V9lChoBmgJaA9DCLitLbwoS/BAlIaUUpRoFU3oA2gWR0Ci8nNt65XmdX2UKGgGaAloD0MIA+likw4x8UCUhpRSlGgVTegDaBZHQKLybS2phnd1fZQoaAZoCWgPQwi6FcJqoQLqQJSGlFKUaBVN6ANoFkdAovJnIZIg/3V9lChoBmgJaA9DCFKBky19YvJAlIaUUpRoFU3oA2gWR0Ci8mFZgXuWdX2UKGgGaAloD0MIQq8/iWnz60CUhpRSlGgVTegDaBZHQKLyW2sq8UV1fZQoaAZoCWgPQwiY3v4cmCT0QJSGlFKUaBVN6ANoFkdAovJVI5HVgHV9lChoBmgJaA9DCP2C3fCGRvJAlIaUUpRoFU3oA2gWR0Ci8k9vsJIEdX2UKGgGaAloD0MIR1hUxLEQ6UCUhpRSlGgVTegDaBZHQKLySU1Q66t1fZQoaAZoCWgPQwiU2SATnRboQJSGlFKUaBVN6ANoFkdAovJEHv+fiHV9lChoBmgJaA9DCBh9BWkF3+tAlIaUUpRoFU3oA2gWR0Ci8aVDSgGsdX2UKGgGaAloD0MIHhmrzWmJ6kCUhpRSlGgVTegDaBZHQKLxnh4MWoF1fZQoaAZoCWgPQwgw2uOFSiTrQJSGlFKUaBVN6ANoFkdAovGX4qPOp3V9lChoBmgJaA9DCOIGfD4rl/JAlIaUUpRoFU3oA2gWR0Ci8ZFbmlqKdX2UKGgGaAloD0MIuTgqt8/M8kCUhpRSlGgVTegDaBZHQKLxi2rGR3h1fZQoaAZoCWgPQwhgkPTpGjvtQJSGlFKUaBVN6ANoFkdAovGFMh5gPXV9lChoBmgJaA9DCIHR5U02v+9AlIaUUpRoFU3oA2gWR0CjR2F/hESedX2UKGgGaAloD0MIQuxMIdfJ6kCUhpRSlGgVTegDaBZHQKNHWTCcf/51fZQoaAZoCWgPQwgziXpBIMnwQJSGlFKUaBVN6ANoFkdAo0dS5oXbd3V9lChoBmgJaA9DCE+y1aUghfNAlIaUUpRoFU3oA2gWR0CjR0z/ZM+NdX2UKGgGaAloD0MIaYtr/Bq38ECUhpRSlGgVTegDaBZHQKNHR47ihnJ1fZQoaAZoCWgPQwigbqBA2LnvQJSGlFKUaBVN6ANoFkdAo0dBxBE8aHV9lChoBmgJaA9DCJ3zU9zmF/BAlIaUUpRoFU3oA2gWR0CjRzwizLOidX2UKGgGaAloD0MIz79dtu3c8UCUhpRSlGgVTegDaBZHQKNHNyBClad1fZQoaAZoCWgPQwin5nKDEg/vQJSGlFKUaBVN6ANoFkdAo0cxRsMy8HV9lChoBmgJaA9DCPtal5q/Q/JAlIaUUpRoFU3oA2gWR0CjRywwK0D2dX2UKGgGaAloD0MItybd1tZF80CUhpRSlGgVTegDaBZHQKNGjfZ26kJ1fZQoaAZoCWgPQwjuBPuvtQDqQJSGlFKUaBVN6ANoFkdAo0aHIsAeaXV9lChoBmgJaA9DCFEWvn7wG/RAlIaUUpRoFU3oA2gWR0CjRoGbsniOdX2UKGgGaAloD0MISdV2E/9n8ECUhpRSlGgVTegDaBZHQKNGe30f5k91fZQoaAZoCWgPQwjDnQsjDC3tQJSGlFKUaBVN6ANoFkdAo0Z1z2exwHV9lChoBmgJaA9DCCP1nkrKK/NAlIaUUpRoFU3oA2gWR0CjRm+RoysTdX2UKGgGaAloD0MI8Wd4synJ8ECUhpRSlGgVTegDaBZHQKNmyl8gIQh1fZQoaAZoCWgPQwgTSIldsmH1QJSGlFKUaBVN6ANoFkdAo2bCGL1mJ3V9lChoBmgJaA9DCCKMn0Z2VudAlIaUUpRoFU3oA2gWR0CjZrxjriVCdX2UKGgGaAloD0MIZARU+ClF9UCUhpRSlGgVTegDaBZHQKNmtqlgtvp1fZQoaAZoCWgPQwjPTDCc9MHrQJSGlFKUaBVN6ANoFkdAo2axTdcjaHV9lChoBmgJaA9DCGspIK3zs/BAlIaUUpRoFU3oA2gWR0CjZqt/nW8RdX2UKGgGaAloD0MIp8mMN4Qg8UCUhpRSlGgVTegDaBZHQKNmpVsk6cR1fZQoaAZoCWgPQwj1Y5N8rNf0QJSGlFKUaBVN6ANoFkdAo2af974SH3V9lChoBmgJaA9DCBaiQyD9FPFAlIaUUpRoFU3oA2gWR0CjZposZpBYdX2UKGgGaAloD0MIAFeyYwd79ECUhpRSlGgVTegDaBZHQKNmlQNTcZd1fZQoaAZoCWgPQwj9g0gGoQnyQJSGlFKUaBVN6ANoFkdAo2X2f29L6HV9lChoBmgJaA9DCLhYUQOBlPBAlIaUUpRoFU3oA2gWR0CjZfA+6iCbdX2UKGgGaAloD0MIbO19Ks9g7ECUhpRSlGgVTegDaBZHQKNl6uHvc8F1fZQoaAZoCWgPQwjX+432LyrsQJSGlFKUaBVN6ANoFkdAo2Xk7yQPqnV9lChoBmgJaA9DCF/RrRfJKvFAlIaUUpRoFU3oA2gWR0CjZd9u5z5odX2UKGgGaAloD0MIjkC8rsl17kCUhpRSlGgVTegDaBZHQKNl2Wi1y/91fZQoaAZoCWgPQwgNjLysbLzxQJSGlFKUaBVN6ANoFkdAo7fcCzTnaHV9lChoBmgJaA9DCOz4L5Acn+1AlIaUUpRoFU3oA2gWR0Cjt9K/20zCdX2UKGgGaAloD0MIO/vKg5jk8UCUhpRSlGgVTegDaBZHQKO3zCx/ust1fZQoaAZoCWgPQwgteqfCnovxQJSGlFKUaBVN6ANoFkdAo7fF+NLlFXV9lChoBmgJaA9DCB9JSQ8OVu5AlIaUUpRoFU3oA2gWR0Cjt8AOJ+DwdX2UKGgGaAloD0MInnk57KzO8UCUhpRSlGgVTegDaBZHQKO3uhufmLd1fZQoaAZoCWgPQwjQYb48JOjsQJSGlFKUaBVN6ANoFkdAo7ez06HTJHV9lChoBmgJaA9DCMug2mBJUfFAlIaUUpRoFU3oA2gWR0Cjt64hMajvdX2UKGgGaAloD0MI3h/v1SLN80CUhpRSlGgVTegDaBZHQKO3p+BH09R1fZQoaAZoCWgPQwg/bypSxfP0QJSGlFKUaBVN6ANoFkdAo7eiKcd5p3V9lChoBmgJaA9DCEfmkb+7yOxAlIaUUpRoFU3oA2gWR0CjtwMzuWrwdX2UKGgGaAloD0MIPbX6qoIQ80CUhpRSlGgVTegDaBZHQKO2+/sVtXR1fZQoaAZoCWgPQwjZk8Am7/byQJSGlFKUaBVN6ANoFkdAo7b18/lhgHV9lChoBmgJaA9DCD5ZMdzkGu5AlIaUUpRoFU3oA2gWR0Cjtu+fZmI1dX2UKGgGaAloD0MIlE25wg0u8UCUhpRSlGgVTegDaBZHQKO26bMHKOl1fZQoaAZoCWgPQwgAN4tXkWbxQJSGlFKUaBVN6ANoFkdAo7bjBuXNT3V9lChoBmgJaA9DCMKk+Hj9ufFAlIaUUpRoFU3oA2gWR0Cj1+iEHt4SdX2UKGgGaAloD0MItwvN9bsj80CUhpRSlGgVTegDaBZHQKPX3zBhx5t1fZQoaAZoCWgPQwhgIt56nibxQJSGlFKUaBVN6ANoFkdAo9fYprk8zXV9lChoBmgJaA9DCOzeigTRH/FAlIaUUpRoFU3oA2gWR0Cj19Jswco6dX2UKGgGaAloD0MI0o2wKLfL7kCUhpRSlGgVTegDaBZHQKPXzKlHjId1fZQoaAZoCWgPQwiQLjatdizxQJSGlFKUaBVN6ANoFkdAo9fGitaIN3V9lChoBmgJaA9DCHszar6KmO9AlIaUUpRoFU3oA2gWR0Cj18AVXV9XdX2UKGgGaAloD0MIpHA9ik3U80CUhpRSlGgVTegDaBZHQKPXukSmIj51fZQoaAZoCWgPQwhAprVp2E3xQJSGlFKUaBVN6ANoFkdAo9e0PBi1A3V9lChoBmgJaA9DCPSKp551K/NAlIaUUpRoFU3oA2gWR0Cj166G5+YudX2UKGgGaAloD0MI2/tUVccz+ECUhpRSlGgVTegDaBZHQKPXD7sv7Fd1fZQoaAZoCWgPQwiDF32FZJryQJSGlFKUaBVN6ANoFkdAo9cIjnmq53V9lChoBmgJaA9DCP9eCo/rW+tAlIaUUpRoFU3oA2gWR0Cj1wJcHGCJdX2UKGgGaAloD0MIwJZX7lVO8kCUhpRSlGgVTegDaBZHQKPW/CPZIxx1fZQoaAZoCWgPQwhfz9csNLHtQJSGlFKUaBVN6ANoFkdAo9b2YD1XeXV9lChoBmgJaA9DCMKKU61z6PJAlIaUUpRoFU3oA2gWR0Cj1u/DUExJdWUu"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 350, "observation_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "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", "dtype": "float64", "_shape": [376], "low": "[-inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf\n -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf\n -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf\n -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf\n -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf\n -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf\n -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf\n -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf\n -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf\n -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf\n -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf\n -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf\n -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf\n -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf\n -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf\n -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf\n -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf\n -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf\n -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf\n -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf\n -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf\n -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf\n -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf\n -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf\n -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf\n -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf\n -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf]", "high": "[inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf\n inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf\n inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf\n inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf\n inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf\n inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf\n inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf\n inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf\n inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf\n inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf\n inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf\n inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf\n inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf\n inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf\n inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf\n inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf\n inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf\n inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf\n inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf\n inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf\n inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf]", "bounded_below": "[False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False]", "bounded_above": "[False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False]", "_np_random": null}, "action_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "_shape": [17], "low": "[-0.4 -0.4 -0.4 -0.4 -0.4 -0.4 -0.4 -0.4 -0.4 -0.4 -0.4 -0.4 -0.4 -0.4\n -0.4 -0.4 -0.4]", "high": "[0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4]", "bounded_below": "[ True  True  True  True  True  True  True  True  True  True  True  True\n  True  True  True  True  True]", "bounded_above": "[ True  True  True  True  True  True  True  True  True  True  True  True\n  True  True  True  True  True]", "_np_random": "RandomState(MT19937)"}, "n_envs": 16, "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:": "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"}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "system_info": {"OS": "Linux-5.10.147+-x86_64-with-glibc2.31 # 1 SMP Sat Dec 10 16:00:40 UTC 2022", "Python": "3.10.11", "Stable-Baselines3": "1.8.0", "PyTorch": "2.0.0+cu118", "GPU Enabled": "True", "Numpy": "1.22.4", "Gym": "0.21.0"}}