{"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 0x798c8ecd9580>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x798c8ecd9620>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x798c8ecd96c0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x798c8ecd9760>", "_build": "<function ActorCriticPolicy._build at 0x798c8ecd9800>", "forward": "<function ActorCriticPolicy.forward at 0x798c8ecd98a0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x798c8ecd9940>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x798c8ecd99e0>", "_predict": "<function ActorCriticPolicy._predict at 0x798c8ecd9a80>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x798c8ecd9b20>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x798c8ecd9bc0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x798c8ecd9c60>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x798c8ec3a240>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1748416478132209754, "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:": "gAWVhAAAAAAAAACME251bXB5Ll9jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksQhZSMAUOUdJRSlC4="}, "_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:": "gAWV3AAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFm51bXB5Ll9jb3JlLm11bHRpYXJyYXmUjAZzY2FsYXKUk5SMBW51bXB5lIwFZHR5cGWUk5SMAmk4lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGJDCAQAAAAAAAAAlIaUUpSMBXN0YXJ0lGgIaA5DCAAAAAAAAAAAlIaUUpSMBl9zaGFwZZQpjAVkdHlwZZRoDowKX25wX3JhbmRvbZROdWIu", "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-6.1.123+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sun Mar 30 16:01:29 UTC 2025", "Python": "3.11.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.6.0+cu124", "GPU Enabled": "True", "Numpy": "2.0.2", "Cloudpickle": "3.1.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}