{"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 0x7853de92df80>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7853de92e020>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7853de92e0c0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7853de92e160>", "_build": "<function ActorCriticPolicy._build at 0x7853de92e200>", "forward": "<function ActorCriticPolicy.forward at 0x7853de92e2a0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7853de92e340>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7853de92e3e0>", "_predict": "<function ActorCriticPolicy._predict at 0x7853de92e480>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7853de92e520>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7853de92e5c0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7853de92e660>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7853dea81940>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1740201246245762693, "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": 248, "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": 0.999, "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:": "gAWV1gIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwiVAZcAiQFTAJROhZQpjAFflIWUjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjExL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lIwEZnVuY5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUS4RDCPiAANgPEogKlEMAlIwDdmFslIWUKXSUUpR9lCiMC19fcGFja2FnZV9flIwYc3RhYmxlX2Jhc2VsaW5lczMuY29tbW9ulIwIX19uYW1lX1+UjB5zdGFibGVfYmFzZWxpbmVzMy5jb21tb24udXRpbHOUjAhfX2ZpbGVfX5SMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTEvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUdU5OaACMEF9tYWtlX2VtcHR5X2NlbGyUk5QpUpSFlHSUUpRoAIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaCF9lH2UKGgYjARmdW5jlIwMX19xdWFsbmFtZV9flIwZY29uc3RhbnRfZm4uPGxvY2Fscz4uZnVuY5SMD19fYW5ub3RhdGlvbnNfX5R9lIwOX19rd2RlZmF1bHRzX1+UTowMX19kZWZhdWx0c19flE6MCl9fbW9kdWxlX1+UaBmMB19fZG9jX1+UTowLX19jbG9zdXJlX1+UaACMCl9tYWtlX2NlbGyUk5RHP8mZmZmZmZqFlFKUhZSMF19jbG91ZHBpY2tsZV9zdWJtb2R1bGVzlF2UjAtfX2dsb2JhbHNfX5R9lHWGlIZSMC4="}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "gAWV1gIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwiVAZcAiQFTAJROhZQpjAFflIWUjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjExL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lIwEZnVuY5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUS4RDCPiAANgPEogKlEMAlIwDdmFslIWUKXSUUpR9lCiMC19fcGFja2FnZV9flIwYc3RhYmxlX2Jhc2VsaW5lczMuY29tbW9ulIwIX19uYW1lX1+UjB5zdGFibGVfYmFzZWxpbmVzMy5jb21tb24udXRpbHOUjAhfX2ZpbGVfX5SMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTEvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUdU5OaACMEF9tYWtlX2VtcHR5X2NlbGyUk5QpUpSFlHSUUpRoAIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaCF9lH2UKGgYjARmdW5jlIwMX19xdWFsbmFtZV9flIwZY29uc3RhbnRfZm4uPGxvY2Fscz4uZnVuY5SMD19fYW5ub3RhdGlvbnNfX5R9lIwOX19rd2RlZmF1bHRzX1+UTowMX19kZWZhdWx0c19flE6MCl9fbW9kdWxlX1+UaBmMB19fZG9jX1+UTowLX19jbG9zdXJlX1+UaACMCl9tYWtlX2NlbGyUk5RHPzOpKjBVMmGFlFKUhZSMF19jbG91ZHBpY2tsZV9zdWJtb2R1bGVzlF2UjAtfX2dsb2JhbHNfX5R9lHWGlIZSMC4="}, "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": "3.11.11", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.5.1+cu124", "GPU Enabled": "True", "Numpy": "1.26.4", "Cloudpickle": "3.1.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}