| {"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 0x7ca815ccdfc0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7ca815cce050>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7ca815cce0e0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7ca815cce170>", "_build": "<function ActorCriticPolicy._build at 0x7ca815cce200>", "forward": "<function ActorCriticPolicy.forward at 0x7ca815cce290>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7ca815cce320>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7ca815cce3b0>", "_predict": "<function ActorCriticPolicy._predict at 0x7ca815cce440>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7ca815cce4d0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7ca815cce560>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7ca815cce5f0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7ca815cd8380>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 2031616, "_total_timesteps": 2000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1710562859884856086, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAAECdlj3s2Y65PL8Avv6ZwbRTLtk5JhgcNAAAgD8AAIA/LcETPgW43LvbwQc8MOpAuktgJ7361yK7AACAPwAAgD9N0lg9rgGFujlFyzdk/b8yGDawOu1P7bYAAIA/AACAP/M50L2foaY8ppCUPp7LCr4icN099RvjvAAAAAAAAAAAmjk9vR9tirnM2gk4KxsPM2zC5DuFYye3AACAPwAAgD9mSZw9FFagOcJNlDorgGw1gf2ROh//sLkAAIA/AAAAAGDkBT5EUpE/hrPwPiudRr+cRxw+TFAiPgAAAAAAAAAAZl7dO6lYeT/ggOI8zKyEv4QpEjv4lWu9AAAAAAAAAAAtOg4+7LnSu5teXzxzM7O6xv8zvUM9l7sAAIA/AACAP60KpT5UWO8+Jei5vLS/Bb+9cno+o7/7vQAAAAAAAAAAzb2tPPgBtz+DvJY+T5kjPY5shTsUKDM9AAAAAAAAAAAz0yY+z3JjvPLQWTuD74S5y5nCveHSjroAAIA/AACAPwD2ITyFI825baIqODMTH69dizK5vORHtwAAgD8AAIA/jVYbPo8/VbzGzO44mgb6tvCMw71i7SK4AACAPwAAgD8wBII+iL+APmPWcb5WN+G+XteuPSJu0r0AAAAAAAAAAMbjOz4SrO08j3OtvkEcur7ByC8+DwMvvgAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksQSwiGlIwBQ5R0lFKULg=="}, "_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:": "gAWV5wsAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpRHQHJn0zwc5sGMAWyUS+aMAXSUR0Clo+YekpI+dX2UKGgGR0ByUjxVhkRSaAdLnmgIR0Clo/vFWGRFdX2UKGgGR0BzVvb5/LDAaAdL42gIR0ClpAq3VkMDdX2UKGgGR0BwrBtgrpaBaAdLsWgIR0ClpEwJgLJCdX2UKGgGR0ByM9nmJWNnaAdLz2gIR0ClpFXRoh6jdX2UKGgGR0BlpFSXMQmNaAdN6ANoCEdApaTn4REncHV9lChoBkdAc0cy1NQCS2gHS/hoCEdApaUP0NBnjHV9lChoBkdATW0gfU4JeGgHS2hoCEdApaUcU9IPLHV9lChoBkdAcSWokiUxEmgHS8RoCEdApaV72criEXV9lChoBkdAdGg26TW5H2gHS+RoCEdApaWWvyLAHnV9lChoBkdAbisIiTt9hWgHS6ZoCEdApaXDAk9lmXV9lChoBkdAcFXlg+hXbWgHS7ZoCEdApaZO1MM7VHV9lChoBkdAcutN8ma6SWgHS9RoCEdApaZptgrpaHV9lChoBkdAQMeh4+r2g2gHS29oCEdApadJf2K2rnV9lChoBkdAbz1z8P4EfWgHS6RoCEdApadYB7u2JHV9lChoBkdAcJBQT238XWgHS6xoCEdApadfrdFfA3V9lChoBkdAcXOaePJaJWgHS5loCEdApad090RvnHV9lChoBkdAc1M+i8FpwmgHS9loCEdApaiaONo8IXV9lChoBkdAYoiNp/PPcGgHTegDaAhHQKWooZWq95B1fZQoaAZHQHCyFAzHjp9oB0usaAhHQKWo4+X7cfx1fZQoaAZHQHH0gDaGpMpoB0vPaAhHQKWpbbAUL2J1fZQoaAZHQHD5jbFjurpoB0vJaAhHQKWqEE5hjON1fZQoaAZHQHE3/PX05ENoB0unaAhHQKWqjCSA6Ml1fZQoaAZHQHKtfgzguRNoB0vMaAhHQKWrdQMQVbl1fZQoaAZHQHIbgydnTRZoB0v5aAhHQKWrlKMefZp1fZQoaAZHQHHnJudf9gpoB0ulaAhHQKWrmc3l0YF1fZQoaAZHQHBxOZCv5gxoB0ukaAhHQKWro2aUiY91fZQoaAZHQHJQo8lolD5oB0uyaAhHQKWry8Yht+F1fZQoaAZHQG+RVWCEpRZoB0uaaAhHQKWsR5nlGPR1fZQoaAZHQHEeqbSZ0CBoB0uraAhHQKWs0NCqp991fZQoaAZHQHIm3/T9bX9oB0vqaAhHQKWs1mV7hNx1fZQoaAZHQHHqmxIJ7cBoB0uaaAhHQKWs9/SYw7F1fZQoaAZHQHJVqY3Ns31oB0uTaAhHQKWtTFx4ptt1fZQoaAZHQHK2pbY9Pk9oB0v1aAhHQKWuE1LJ0XB1fZQoaAZHQGDVwUHpr1xoB03oA2gIR0Clrhhx5s0pdX2UKGgGR0BxYTeLvTgEaAdLqmgIR0ClrsWUB4lhdX2UKGgGR0Bz8WhDgIhRaAdL2mgIR0ClrvXUQTVUdX2UKGgGR0ByvgEOiFj/aAdLvWgIR0Clrxll05lwdX2UKGgGR0Bw2NDOTq0MaAdLx2gIR0Clry+ruIAPdX2UKGgGR0BxsRa/yoXLaAdLxWgIR0Clr2ra/RE4dX2UKGgGR0By5xakhzNmaAdLlmgIR0Clr7JnpSrHdX2UKGgGR0BxzEXizcASaAdLumgIR0Clr7KODJ2ddX2UKGgGR0BwHg5MlC1JaAdLpWgIR0Clr9RNRFZxdX2UKGgGR0BwhYbNr0rcaAdLvGgIR0ClsDx1HOKPdX2UKGgGR0BwgYUpNKywaAdLp2gIR0ClsErM1TBJdX2UKGgGR0Bu/6D9OymiaAdLkmgIR0ClsU9yLhrFdX2UKGgGR0BnhbewcHW0aAdN6ANoCEdApbFdf9gndHV9lChoBkdAcxNdTHbRGGgHS9loCEdApbHdVBD5TXV9lChoBkdAcftnGsFMZmgHS69oCEdApbIEwco6S3V9lChoBkdAcL+e7L+xW2gHS69oCEdApbI+cBltj3V9lChoBkdAcXxj/dZaFGgHS6RoCEdApbJM7bL2YnV9lChoBkdAcMOK0UoKD2gHS5poCEdApbJtjmSyMXV9lChoBkdAcLwrwvxpc2gHS6toCEdApbK/BP9DQnV9lChoBkdAczcNnXd0rGgHS+JoCEdApbMgvg3tKXV9lChoBkdAcqcw1BMSK2gHS8JoCEdApbNa2+fyw3V9lChoBkdAcl5YjjaPCGgHS61oCEdApbNqIFeOXHV9lChoBkdAclf37UG3WmgHS8NoCEdApbPhLwnYx3V9lChoBkdAO0qrJbMX8GgHS2RoCEdApbRTkU9IPXV9lChoBkdAcSORJVbRnmgHS6RoCEdApbRb987ZF3V9lChoBkdAcQ+lRgqmTGgHS7toCEdApbTT9MsYmHV9lChoBkdAcT53wTdtVWgHS45oCEdApbT2DOC5E3V9lChoBkdAcdTaCtihFmgHS6toCEdApbUNeOXE63V9lChoBkdAcKOWn0kGA2gHS7RoCEdApbWjj5sTFnV9lChoBkdAcp2yWRigCmgHS8ZoCEdApbXC9PDYRXV9lChoBkdAb/ylqJuVHGgHS6RoCEdApbaBgw482nV9lChoBkdAcutdZq20A2gHS9BoCEdApbazc/MW43V9lChoBkdAclq42CNCJGgHS7poCEdApbbfD1oQF3V9lChoBkdAc329ZzPrwGgHS+BoCEdApbdktbs4UHV9lChoBkdAb7eJUHY6GWgHS6NoCEdApbd05dWyT3V9lChoBkdAcgWoXsPatmgHS75oCEdApbeCy4Wk8HV9lChoBkdAcZq9ZA6dUmgHS61oCEdApberyrgfl3V9lChoBkdAcM68zQ/oq2gHS51oCEdApbfav5gw5HV9lChoBkdAZOyVN5+pfmgHTegDaAhHQKW4OOTaCcx1fZQoaAZHQHCkXUc4o7VoB0umaAhHQKW4PqBVdX11fZQoaAZHQHJeMHB1s+FoB0u9aAhHQKW5JmmLtNV1fZQoaAZHQHIe/QWvbGpoB0ucaAhHQKW5YRGMGX51fZQoaAZHQGOEWO6unuRoB03oA2gIR0CluZIrOJLvdX2UKGgGR0BwfLC0ngHeaAdLoWgIR0CluaeYc/+sdX2UKGgGR0BxppbgTAWSaAdL0mgIR0Cluaf8EV32dX2UKGgGR0ByU9KWcBluaAdLmWgIR0CluavNeMQ3dX2UKGgGR0A5lVWCEpRXaAdLWmgIR0Cluc9rO7g9dX2UKGgGR0BwdY6o2n89aAdLiWgIR0Clud9o371qdX2UKGgGR0BxXnozN2TxaAdLkGgIR0Clue0rCm/GdX2UKGgGR0Bz0dhw2l2vaAdLu2gIR0Cluqr+o99udX2UKGgGR0BwtTbYbsF/aAdLuGgIR0CluvHuAqd6dX2UKGgGR0BxHHNke6qbaAdLxGgIR0Cluvv1DjR2dX2UKGgGR0Bvv74BV+7UaAdLqWgIR0CluwnIQvpRdX2UKGgGR0Bv+4k5ZKWcaAdLlmgIR0Clu6Dp9qk/dX2UKGgGR0Bx9Vx3mmtRaAdLnWgIR0ClvDoakyk9dX2UKGgGR0BxZJvl2eQNaAdLrGgIR0ClvGNVBD5TdX2UKGgGR0BwY3KLbYbsaAdLp2gIR0ClvGM8PnSwdX2UKGgGR0Byk8yyleniaAdLr2gIR0ClvIbWuoxYdX2UKGgGR0BxHlMlC1JEaAdLqmgIR0ClvK5uhsZYdX2UKGgGR0ByAfYYixFBaAdLuWgIR0ClvOIi1RcedX2UKGgGR0ByFcAdXDFZaAdLhWgIR0ClvTygf2bodX2UKGgGR0Bzz4UUO/cnaAdL0mgIR0ClvXp2MbWFdX2UKGgGR0BlhVz8xbjcaAdN6ANoCEdApb2nixVyWHV9lChoBkdAcvMVjqfOEGgHS8hoCEdApb55U96kZnV9lChoBkdAcfJ+KCQLeGgHS6ZoCEdApb5+Pkq+anV9lChoBkdAcjezU7Sy+2gHS99oCEdApb7QcghbGHVlLg=="}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 620, "observation_space": {":type:": "<class 'gymnasium.spaces.box.Box'>", ":serialized:": "gAWVdgIAAAAAAACMFGd5bW5hc2l1bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lIwFZHR5cGWUk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMDWJvdW5kZWRfYmVsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWCAAAAAAAAAABAQEBAQEBAZRoCIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksIhZSMAUOUdJRSlIwNYm91bmRlZF9hYm92ZZRoESiWCAAAAAAAAAABAQEBAQEBAZRoFUsIhZRoGXSUUpSMBl9zaGFwZZRLCIWUjANsb3eUaBEoliAAAAAAAAAAAAC0wgAAtMIAAKDAAACgwNsPScAAAKDAAAAAgAAAAICUaAtLCIWUaBl0lFKUjARoaWdolGgRKJYgAAAAAAAAAAAAtEIAALRCAACgQAAAoEDbD0lAAACgQAAAgD8AAIA/lGgLSwiFlGgZdJRSlIwIbG93X3JlcHKUjFtbLTkwLiAgICAgICAgLTkwLiAgICAgICAgIC01LiAgICAgICAgIC01LiAgICAgICAgIC0zLjE0MTU5MjcgIC01LgogIC0wLiAgICAgICAgIC0wLiAgICAgICBdlIwJaGlnaF9yZXBylIxTWzkwLiAgICAgICAgOTAuICAgICAgICAgNS4gICAgICAgICA1LiAgICAgICAgIDMuMTQxNTkyNyAgNS4KICAxLiAgICAgICAgIDEuICAgICAgIF2UjApfbnBfcmFuZG9tlE51Yi4=", "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": 2048, "gamma": 0.99, "gae_lambda": 0.95, "ent_coef": 0.02, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 128, "n_epochs": 10, "clip_range": {":type:": "<class 'function'>", ":serialized:": "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"}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "system_info": {"OS": "Linux-6.1.58+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sat Nov 18 15:31:17 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.2.1+cu121", "GPU Enabled": "False", "Numpy": "1.25.2", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}} |