{"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 0x7e461a0e2830>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7e461a0e28c0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7e461a0e2950>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7e461a0e29e0>", "_build": "<function ActorCriticPolicy._build at 0x7e461a0e2a70>", "forward": "<function ActorCriticPolicy.forward at 0x7e461a0e2b00>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7e461a0e2b90>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7e461a0e2c20>", "_predict": "<function ActorCriticPolicy._predict at 0x7e461a0e2cb0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7e461a0e2d40>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7e461a0e2dd0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7e461a0e2e60>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7e461a087d00>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1736865294396306328, "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": 620, "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": 0.9999, "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:": "gAWVrQIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTAvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUjARmdW5jlEuEQwIEAZSMA3ZhbJSFlCl0lFKUfZQojAtfX3BhY2thZ2VfX5SMGHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbpSMCF9fbmFtZV9flIwec3RhYmxlX2Jhc2VsaW5lczMuY29tbW9uLnV0aWxzlIwIX19maWxlX1+UjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjEwL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUaACMEl9mdW5jdGlvbl9zZXRzdGF0ZZSTlGgffZR9lChoFowEZnVuY5SMDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgXjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz/JmZmZmZmahZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"}, "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"}}