{"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 0x2861aa840>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x2861aa8e0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x2861aa980>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x2861aaa20>", "_build": "<function ActorCriticPolicy._build at 0x2861aaac0>", "forward": "<function ActorCriticPolicy.forward at 0x2861aab60>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x2861aac00>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x2861aaca0>", "_predict": "<function ActorCriticPolicy._predict at 0x2861aad40>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x2861aade0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x2861aae80>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x2861aaf20>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x285d63280>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1702292193916309000, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": null, "_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": 496, "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:": "gAWV/QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgLjAJpOJSJiIeUUpQoSwNoD05OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu", "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:": "gAWV5QIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwiVAZcAiQFTAJROhZQpjAFflIWUjGAvVXNlcnMvZXh4eHN0aC9taW5pY29uZGEzL2VudnMvcmwvbGliL3B5dGhvbjMuMTEvc2l0ZS1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUjARmdW5jlIwZY29uc3RhbnRfZm4uPGxvY2Fscz4uZnVuY5RLhEMI+IAA2A8SiAqUQwCUjAN2YWyUhZQpdJRSlH2UKIwLX19wYWNrYWdlX1+UjBhzdGFibGVfYmFzZWxpbmVzMy5jb21tb26UjAhfX25hbWVfX5SMHnN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi51dGlsc5SMCF9fZmlsZV9flIxgL1VzZXJzL2V4eHhzdGgvbWluaWNvbmRhMy9lbnZzL3JsL2xpYi9weXRob24zLjExL3NpdGUtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUaACMEl9mdW5jdGlvbl9zZXRzdGF0ZZSTlGghfZR9lChoGGgNjAxfX3F1YWxuYW1lX1+UaA6MD19fYW5ub3RhdGlvbnNfX5R9lIwOX19rd2RlZmF1bHRzX1+UTowMX19kZWZhdWx0c19flE6MCl9fbW9kdWxlX1+UaBmMB19fZG9jX1+UTowLX19jbG9zdXJlX1+UaACMCl9tYWtlX2NlbGyUk5RHP8mZmZmZmZqFlFKUhZSMF19jbG91ZHBpY2tsZV9zdWJtb2R1bGVzlF2UjAtfX2dsb2JhbHNfX5R9lHWGlIZSMC4="}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "gAWV5QIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwiVAZcAiQFTAJROhZQpjAFflIWUjGAvVXNlcnMvZXh4eHN0aC9taW5pY29uZGEzL2VudnMvcmwvbGliL3B5dGhvbjMuMTEvc2l0ZS1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUjARmdW5jlIwZY29uc3RhbnRfZm4uPGxvY2Fscz4uZnVuY5RLhEMI+IAA2A8SiAqUQwCUjAN2YWyUhZQpdJRSlH2UKIwLX19wYWNrYWdlX1+UjBhzdGFibGVfYmFzZWxpbmVzMy5jb21tb26UjAhfX25hbWVfX5SMHnN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi51dGlsc5SMCF9fZmlsZV9flIxgL1VzZXJzL2V4eHhzdGgvbWluaWNvbmRhMy9lbnZzL3JsL2xpYi9weXRob24zLjExL3NpdGUtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUaACMEl9mdW5jdGlvbl9zZXRzdGF0ZZSTlGghfZR9lChoGGgNjAxfX3F1YWxuYW1lX1+UaA6MD19fYW5ub3RhdGlvbnNfX5R9lIwOX19rd2RlZmF1bHRzX1+UTowMX19kZWZhdWx0c19flE6MCl9fbW9kdWxlX1+UaBmMB19fZG9jX1+UTowLX19jbG9zdXJlX1+UaACMCl9tYWtlX2NlbGyUk5RHPzOpKjBVMmGFlFKUhZSMF19jbG91ZHBpY2tsZV9zdWJtb2R1bGVzlF2UjAtfX2dsb2JhbHNfX5R9lHWGlIZSMC4="}, "system_info": {"OS": "macOS-13.4.1-arm64-i386-64bit Darwin Kernel Version 22.5.0: Thu Jun  8 22:22:20 PDT 2023; root:xnu-8796.121.3~7/RELEASE_ARM64_T6000", "Python": "3.11.0", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.1.1", "GPU Enabled": "False", "Numpy": "1.26.2", "Cloudpickle": "3.0.0", "Gymnasium": "0.28.1", "OpenAI Gym": "0.26.2"}}