{"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 0x79f4ce3a4c10>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x79f4ce3a4ca0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x79f4ce3a4d30>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x79f4ce3a4dc0>", "_build": "<function ActorCriticPolicy._build at 0x79f4ce3a4e50>", "forward": "<function ActorCriticPolicy.forward at 0x79f4ce3a4ee0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x79f4ce3a4f70>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x79f4ce3a5000>", "_predict": "<function ActorCriticPolicy._predict at 0x79f4ce3a5090>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x79f4ce3a5120>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x79f4ce3a51b0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x79f4ce3a5240>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x79f4ce345780>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1700758058840678588, "learning_rate": 0.001, "tensorboard_log": null, "_last_obs": null, "_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": 496, "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:": "gAWV/QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgLjAJpOJSJiIeUUpQoSwNoD05OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "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, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "system_info": {"OS": "Linux-5.15.120+-x86_64-with-glibc2.35 # 1 SMP Wed Aug 30 11:19:59 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.1.0+cu118", "GPU Enabled": "False", "Numpy": "1.23.5", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}