{"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 0x7a8805ca4f70>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7a8805ca5000>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7a8805ca5090>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7a8805ca5120>", "_build": "<function ActorCriticPolicy._build at 0x7a8805ca51b0>", "forward": "<function ActorCriticPolicy.forward at 0x7a8805ca5240>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7a8805ca52d0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7a8805ca5360>", "_predict": "<function ActorCriticPolicy._predict at 0x7a8805ca53f0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7a8805ca5480>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7a8805ca5510>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7a8805ca55a0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7a8805c3a500>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1719985471137953648, "learning_rate": 0.0003, "tensorboard_log": null, "_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:": "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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": 0.999, "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-6.1.85+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Tue Jun 18 14:18:04 UTC 2024", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.3.0+cu121", "GPU Enabled": "True", "Numpy": "1.25.2", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}