{ "policy_class": { ":type:": "", ":serialized:": "gASVOwAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMEUFjdG9yQ3JpdGljUG9saWN5lJOULg==", "__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 sde_net_arch: Network architecture for extracting features\n when using gSDE. If None, the latent features from the policy will be used.\n Pass an empty list to use the states as features.\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 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__": "", "_get_constructor_parameters": "", "reset_noise": "", "_build_mlp_extractor": "", "_build": "", "forward": "", "_get_action_dist_from_latent": "", "_predict": "", "evaluate_actions": "", "get_distribution": "", "predict_values": "", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f95e9eb3d50>" }, "verbose": 1, "policy_kwargs": { ":type:": "", ":serialized:": "gASVowAAAAAAAAB9lCiMDGxvZ19zdGRfaW5pdJRK/v///4wKb3J0aG9faW5pdJSJjA9vcHRpbWl6ZXJfY2xhc3OUjBN0b3JjaC5vcHRpbS5ybXNwcm9wlIwHUk1TcHJvcJSTlIwQb3B0aW1pemVyX2t3YXJnc5R9lCiMBWFscGhhlEc/764UeuFHrowDZXBzlEc+5Pi1iONo8YwMd2VpZ2h0X2RlY2F5lEsAdXUu", "log_std_init": -2, "ortho_init": false, "optimizer_class": "", "optimizer_kwargs": { "alpha": 0.99, "eps": 1e-05, "weight_decay": 0 } }, "observation_space": { ":type:": "", ":serialized:": "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", "dtype": "float32", "_shape": [ 28 ], "low": "[-inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf\n -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf]", "high": "[inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf\n inf inf inf inf inf inf inf inf inf inf]", "bounded_below": "[False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False]", "bounded_above": "[False False False False False False False False False False False False\n False False False False False False False False False False False False\n False False False False]", "_np_random": null }, "action_space": { ":type:": "", ":serialized:": "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", "dtype": "float32", "_shape": [ 8 ], "low": "[-1. -1. -1. -1. -1. -1. -1. -1.]", "high": "[1. 1. 1. 1. 1. 1. 1. 1.]", "bounded_below": "[ True True True True True True True True]", "bounded_above": "[ True True True True True True True True]", "_np_random": null }, "n_envs": 4, "num_timesteps": 2000000, "_total_timesteps": 2000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1660723541.215957, "learning_rate": 0.00096, "tensorboard_log": "./tensorboard", "lr_schedule": { ":type:": "", ":serialized:": "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" }, "_last_obs": { ":type:": "", ":serialized:": "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" }, "_last_episode_starts": { ":type:": "", ":serialized:": "gASVjAAAAAAAAACMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMDF9yZWNvbnN0cnVjdJSTlIwFbnVtcHmUjAduZGFycmF5lJOUSwCFlEMBYpSHlFKUKEsBSwSFlGgDjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYolDBAAAAACUdJRiLg==" }, "_last_original_obs": { ":type:": "", ":serialized:": "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" }, "_episode_num": 0, "use_sde": true, "sde_sample_freq": -1, "_current_progress_remaining": 0.0, "ep_info_buffer": { ":type:": "", ":serialized:": "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" }, "ep_success_buffer": { ":type:": "", ":serialized:": "gASVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg==" }, "_n_updates": 62500, "n_steps": 8, "gamma": 0.99, "gae_lambda": 0.9, "ent_coef": 0.0, "vf_coef": 0.4, "max_grad_norm": 0.5, "normalize_advantage": false }