{ "policy_class": { ":type:": "", ":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 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 0x7f8d5f4ff420>" }, "verbose": 1, "policy_kwargs": {}, "observation_space": { ":type:": "", ":serialized:": "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", "dtype": "float32", "_shape": [ 8 ], "low": "[-inf -inf -inf -inf -inf -inf -inf -inf]", "high": "[inf inf inf inf inf inf inf inf]", "bounded_below": "[False False False False False False False False]", "bounded_above": "[False False False False False False False False]", "_np_random": null }, "action_space": { ":type:": "", ":serialized:": "gAWVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu", "n": 4, "_shape": [], "dtype": "int64", "_np_random": null }, "n_envs": 16, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1671702117675130865, "learning_rate": 0.0003, "tensorboard_log": null, "lr_schedule": { ":type:": "", ":serialized:": "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" }, "_last_obs": null, "_last_episode_starts": { ":type:": "", ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg==" }, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.015808000000000044, "ep_info_buffer": { ":type:": "", ":serialized:": "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" }, "ep_success_buffer": { ":type:": "", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg==" }, "_n_updates": 380, "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:": "", ":serialized:": "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" }, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null }