{"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 0x7e0bf5caeb00>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7e0bf5caeb90>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7e0bf5caec20>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7e0bf5caecb0>", "_build": "<function ActorCriticPolicy._build at 0x7e0bf5caed40>", "forward": "<function ActorCriticPolicy.forward at 0x7e0bf5caedd0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7e0bf5caee60>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7e0bf5caeef0>", "_predict": "<function ActorCriticPolicy._predict at 0x7e0bf5caef80>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7e0bf5caf010>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7e0bf5caf0a0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7e0bf5caf130>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7e0bf5c62ec0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 10000384, "_total_timesteps": 10000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1711601556263014770, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAAO1wTT4ebJ4/SZAfP15NGb+FNaM+pGeBPgAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksBSwiGlIwBQ5R0lFKULg=="}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdAAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYBAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwGFlIwBQ5R0lFKULg=="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -3.8399999999993994e-05, "_stats_window_size": 100, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWV5AsAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpRHQHOfkjgQ6IaMAWyUS7yMAXSUR0DS61hXlr/LdX2UKGgGR0ByQD5P/JeWaAdL22gIR0DS62ZlqagFdX2UKGgGR0Bvr6DVYp2EaAdLxWgIR0DS63QNx2jgdX2UKGgGR0ByNYNYr8R+aAdLs2gIR0DS6373/PxAdX2UKGgGR0BzIqS8rZrYaAdLtGgIR0DS64rlA/s3dX2UKGgGR0BygqteUpuuaAdLwWgIR0DS65aQyRCAdX2UKGgGR0BxBUoH9m6HaAdLt2gIR0DS66HlkpZwdX2UKGgGR0Bzc27pV0cPaAdL42gIR0DS7BhWCEpRdX2UKGgGR0Bwq+txMnJDaAdL42gIR0DS7Csmx+rmdX2UKGgGR0Bwz5G3F1jiaAdLv2gIR0DS7DrF0gbIdX2UKGgGR0BzDySDAaegaAdL42gIR0DS7EyKVII4dX2UKGgGR0Bz/dqCYkVvaAdL72gIR0DS7GAzwc5sdX2UKGgGR0Byhhlum78OaAdLv2gIR0DS7HBchTwVdX2UKGgGR0Bxpk6Oo5xSaAdLxmgIR0DS7IHhn8KpdX2UKGgGR0BxME71ZkkKaAdLw2gIR0DS7JOkDZDidX2UKGgGR0BvxWBg/keZaAdL1mgIR0DS7KDigkC4dX2UKGgGR0BxQ9I/Z/TcaAdL0GgIR0DS7K3YUWVNdX2UKGgGR0ByRNk6Lfk4aAdL52gIR0DS7RkCmuTzdX2UKGgGR0Btsze0ojOcaAdNCAFoCEdA0u0pqEeyRnV9lChoBkdAcXvw3HaN/GgHS/FoCEdA0u04+evpyXV9lChoBkdAdD5fra/RFGgHS91oCEdA0u1GiVjZtnV9lChoBkdAchbXw9aEBmgHS7poCEdA0u1SAS39aXV9lChoBkdAcrweWfK6nWgHS7hoCEdA0u1d47A+IXV9lChoBkdAcMMPmgam42gHS8FoCEdA0u1qBMSK33V9lChoBkdAcNSu8scyWWgHS8BoCEdA0u11+OOsDHV9lChoBkdAc1bHf/FR52gHS65oCEdA0u2AwiaAnXV9lChoBkdAcQmxSHdoFmgHS+NoCEdA0u3sGOuJUHV9lChoBkdAchO1qFh5PmgHS8hoCEdA0u34npSrHXV9lChoBkdAcQUu2qkuYmgHS+ZoCEdA0u4HAf+0gXV9lChoBkdAccQcYqG1yGgHS8loCEdA0u4TanrIHXV9lChoBkdAcMfFaB7NS2gHS9ZoCEdA0u4hPRArx3V9lChoBkdAc+mzVMEidWgHS/ZoCEdA0u4wlGPPs3V9lChoBkdAb/fU4rBj4GgHS8RoCEdA0u49E3sHB3V9lChoBkdAcgwEKVpsXWgHS95oCEdA0u5Kj2SMcnV9lChoBkdAcctk+HJtBWgHS8ZoCEdA0u5WuloDgnV9lChoBkdAcqpmXgLqlmgHS89oCEdA0u5j6mfoR3V9lChoBkdAcHiNBWxQi2gHS+hoCEdA0u7PzJZGKHV9lChoBkdAcfYs2vStvGgHS8ZoCEdA0u7caYNRWXV9lChoBkdAcT8pgkTpPmgHS91oCEdA0u7q4PwuunV9lChoBkdAco/MgU1yemgHS+FoCEdA0u745xzaK3V9lChoBkdAceu7OVxCIGgHS7loCEdA0u8Eg3tKI3V9lChoBkdAcp5O7g88tGgHS/xoCEdA0u8U4XXRPXV9lChoBkdAY+wwr1/UfGgHTegDaAhHQNLv3u+qR2d1fZQoaAZHQHOFKyv9tMxoB0vTaAhHQNLv7P3ztkZ1fZQoaAZHQHFdizsyBTZoB0u5aAhHQNLv+pVfeDZ1fZQoaAZHQHDDH05EMLFoB0vqaAhHQNLwCUP1+RZ1fZQoaAZHQHEH6vmozepoB0vdaAhHQNLwFuKwY+B1fZQoaAZHQHKhJCrtE5RoB0v3aAhHQNLwJllGwzN1fZQoaAZHQHGwFjurp7loB0vSaAhHQNLwNVNtZV51fZQoaAZHQG/hQk5ZKWdoB0vbaAhHQNLwQ8K1G9Z1fZQoaAZHQHHADnzQNTdoB0vBaAhHQNLwT2f02+B1fZQoaAZHQHIfjrRjSXtoB0u3aAhHQNLwuIVdonN1fZQoaAZHQHHA2qHXVb1oB0vLaAhHQNLwxM+zMRp1fZQoaAZHQHIt/LHMlkZoB0u9aAhHQNLw0MfFJg91fZQoaAZHQHGt4oE0SAZoB0vbaAhHQNLw3lYMfA91fZQoaAZHQHI8H2ys0YVoB0vMaAhHQNLw62CmMwV1fZQoaAZHQHAD82eg+QloB0vPaAhHQNLw+NIClrN1fZQoaAZHQHI/xxtHhCNoB0vZaAhHQNLxBoXwb2l1fZQoaAZHQHGrRXnyNGVoB0vXaAhHQNLxE88DB/J1fZQoaAZHQHB8KWLP2PFoB0vkaAhHQNLxImZJCjV1fZQoaAZHQHJ/FV5rxiJoB00OAWgIR0DS8TPt8eCDdX2UKGgGR0Bui9WuHN5daAdL22gIR0DS8afzoUzsdX2UKGgGR0Byiz+VC5VfaAdL7WgIR0DS8bZxZMcqdX2UKGgGR0BwLuxZ+x4ZaAdL2WgIR0DS8cVnUUfxdX2UKGgGR0ByTQKD0163aAdLzmgIR0DS8dIM2FWXdX2UKGgGR0By3f9WIXTFaAdLx2gIR0DS8d7JDE3sdX2UKGgGR0By3vTQVsUJaAdLuWgIR0DS8etklNUPdX2UKGgGR0Bxx62Yv38GaAdL6WgIR0DS8fspEx7BdX2UKGgGR0BxESJfpljFaAdLzWgIR0DS8goiA2AHdX2UKGgGR0BxuSR/3FkyaAdN1AFoCEdA0vLq+i8Fp3V9lChoBkdAc0yyJKraNGgHS79oCEdA0vL+w+t8u3V9lChoBkdAceFNOM2m52gHS+toCEdA0vMVXC0ngHV9lChoBkdAcNeVHnU2DWgHS99oCEdA0vMo8XenAXV9lChoBkdAcdo0yP+4smgHS7xoCEdA0vM0cE/0NHV9lChoBkdAbsQZpBX0XmgHS9doCEdA0vNB1hsqKHV9lChoBkdAcSRqgh8pkWgHS/FoCEdA0vNQzV+ZxHV9lChoBkdAcTNfr8iwCGgHS8poCEdA0vNd08NhE3V9lChoBkdAcsblFMIu5GgHS7toCEdA0vNqR/ViF3V9lChoBkdAcrlLKV6eG2gHS9RoCEdA0vN3v1lGw3V9lChoBkdAcq8ews5GSmgHS/ZoCEdA0vPq4+KTCHV9lChoBkdAcSWK0UoKD2gHS/BoCEdA0vP5lYU343V9lChoBkdAcim3LFGXomgHS+5oCEdA0vQI7YChe3V9lChoBkdAcCJxOclPamgHS9FoCEdA0vQVx4IKMXV9lChoBkdAcqRwjt5UtWgHS7RoCEdA0vQiC7sfJXV9lChoBkdAb7Cadc0Lt2gHS8loCEdA0vQuwRoRI3V9lChoBkdAb5rffGdZq2gHS75oCEdA0vQ6LUCq63V9lChoBkdAcC/HVwxWUGgHS81oCEdA0vRGvf0mMXV9lChoBkdARCQP9UCJXWgHS5JoCEdA0vRPdjoZAXV9lChoBkfAOgFTzd1uBWgHS1toCEdA0vRVL26ClXV9lChoBkdAcnaf642CNGgHS9hoCEdA0vS/pEx7A3V9lChoBkdAIFWfChvitWgHS2JoCEdA0vTFw4KhMHV9lChoBkdAc6j85CF9KGgHS8NoCEdA0vTSE0BOpXV9lChoBkdAcPSNlyzXz2gHS8JoCEdA0vTeR8c+7nV9lChoBkdAcNGyXUpd8mgHS8ZoCEdA0vTrA80UGnV9lChoBkdAc+NNGmUGFGgHS/VoCEdA0vT6dGiHqXV9lChoBkdAcrQ/6fra/WgHS9loCEdA0vUIPDYRNHV9lChoBkdAc5gUyYXwb2gHS+toCEdA0vUW33YcvXV9lChoBkdAczNKP4mCy2gHS91oCEdA0vUl5XEIgXV9lChoBkdAcp9iXpnpS2gHS7ZoCEdA0vUxOkLx7XV9lChoBkdAcb4D2JzkqGgHS8toCEdA0vU90cOsk3VlLg=="}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 48830, "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": 1, "n_steps": 2048, "gamma": 0.99, "gae_lambda": 0.95, "ent_coef": 0.0, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 64, "n_epochs": 10, "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": "False", "Numpy": "1.25.2", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}