{"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 0x7dd765ffd240>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7dd765ffd2d0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7dd765ffd360>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7dd765ffd3f0>", "_build": "<function ActorCriticPolicy._build at 0x7dd765ffd480>", "forward": "<function ActorCriticPolicy.forward at 0x7dd765ffd510>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7dd765ffd5a0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7dd765ffd630>", "_predict": "<function ActorCriticPolicy._predict at 0x7dd765ffd6c0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7dd765ffd750>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7dd765ffd7e0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7dd765ffd870>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7dd765fa3cc0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1712859662151967341, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAAJqDNrxc43y6UDatvEGalrQHZ0Q7wxUPNAAAgD8AAIA/M5TbvEjDirqqicI3ZyxstW4HO7vDVNq2AACAPwAAgD8Ad/m8rpWZul1N4Tm3HCe2ACKVuoFJAbkAAIA/AACAPwDkory45su5tyuLOtVqH7Y1Q7+5YNWfuQAAgD8AAIA/c/2APorgPz+yMGO85dqOvh7cVD5+Dc+9AAAAAAAAAABmou68j9YnvM10g7y+/eE8qvGJPU97t70AAIA/AACAPzNEAD32Lj68ruzKvYL1fr3imIq9jWxfvgAAgD8AAIA/M0OcOimwLboygP27dbB/NQPSOjpt/+60AACAPwAAgD/miC69UhjgudKnwbm8szAz2uANuxKbYrMAAIA/AACAPxpcX70puG26KkRLu4WFCThIKIY4GpP0OQAAgD8AAIA/TfMnPYQ3Az9V35e+JqZDvmrVm77tb9U9AAAAAAAAAABmBbC8j/4suoqqDbsEQlY4VPC+OiZwlTkAAIA/AACAP+Y4Q70fTde5rgi/OgmHxbSy8Hq6TiDiuQAAgD8AAIA/M9LbPHuSj7rO2KO7eyK9tmaH2TriRS02AACAPwAAgD8mE7g9duPBPnIe9bw8bWa+4YwhPSrLwb0AAAAAAAAAAJpYaj2CvIo/WswqPozBu74VGic87sK/PAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////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, "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:": "gAWV2wAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgOjApfbnBfcmFuZG9tlE51Yi4=", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "n_steps": 1024, "gamma": 0.99999, "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, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "system_info": {"OS": "Linux-6.1.58+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sat Nov 18 15:31:17 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.2.1+cu121", "GPU Enabled": "True", "Numpy": "1.25.2", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}