{"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 0x781872fa2050>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x781872fa20e0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x781872fa2170>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x781872fa2200>", "_build": "<function ActorCriticPolicy._build at 0x781872fa2290>", "forward": "<function ActorCriticPolicy.forward at 0x781872fa2320>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x781872fa23b0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x781872fa2440>", "_predict": "<function ActorCriticPolicy._predict at 0x781872fa24d0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x781872fa2560>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x781872fa25f0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x781872fa2680>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x781872f10ac0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1734716196123193462, "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:": "gAWVdgIAAAAAAACMFGd5bW5hc2l1bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lIwFZHR5cGWUk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMDWJvdW5kZWRfYmVsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWCAAAAAAAAAABAQEBAQEBAZRoCIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksIhZSMAUOUdJRSlIwNYm91bmRlZF9hYm92ZZRoESiWCAAAAAAAAAABAQEBAQEBAZRoFUsIhZRoGXSUUpSMBl9zaGFwZZRLCIWUjANsb3eUaBEoliAAAAAAAAAAAAC0wgAAtMIAAKDAAACgwNsPScAAAKDAAAAAgAAAAICUaAtLCIWUaBl0lFKUjARoaWdolGgRKJYgAAAAAAAAAAAAtEIAALRCAACgQAAAoEDbD0lAAACgQAAAgD8AAIA/lGgLSwiFlGgZdJRSlIwIbG93X3JlcHKUjFtbLTkwLiAgICAgICAgLTkwLiAgICAgICAgIC01LiAgICAgICAgIC01LiAgICAgICAgIC0zLjE0MTU5MjcgIC01LgogIC0wLiAgICAgICAgIC0wLiAgICAgICBdlIwJaGlnaF9yZXBylIxTWzkwLiAgICAgICAgOTAuICAgICAgICAgNS4gICAgICAgICA1LiAgICAgICAgIDMuMTQxNTkyNyAgNS4KICAxLiAgICAgICAgIDEuICAgICAgIF2UjApfbnBfcmFuZG9tlE51Yi4=", "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 Thu Jun 27 21:05:47 UTC 2024", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.5.1+cu121", "GPU Enabled": "True", "Numpy": "1.26.4", "Cloudpickle": "3.1.0", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}