ppo-LunarLander-v2 / config.json
bob1-bob2's picture
Upload PPO LunarLander-v2 trained agent
526f2c0 verified
{"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 0x7869ef3339c0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7869ef333a60>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7869ef333b00>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7869ef333ba0>", "_build": "<function ActorCriticPolicy._build at 0x7869ef333c40>", "forward": "<function ActorCriticPolicy.forward at 0x7869ef333ce0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7869ef333d80>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7869ef333e20>", "_predict": "<function ActorCriticPolicy._predict at 0x7869ef333ec0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7869ef333f60>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7869ef33c040>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7869ef33c0e0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7869ef4aa680>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1748914499664937961, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdgIAAAAAAACME251bXB5Ll9jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWAAIAAAAAAADmRQM9eDnDPuiEzb2cm06+XKruvCjrXr0AAAAAAAAAALMEZr3D1U26c31Au7wzzrYgJyI7RfJgOgAAgD8AAIA/WgIPPsOhXz+V8wo+C+GYvvHMWT2hTAG9AAAAAAAAAACzu2I9XOMuumsC1ToVx/A1dLZTOhI9/LkAAIA/AACAP02Gsr1cByC6rxUMuYXQW7RNSCW7dfYpOAAAgD8AAIA/AEAdOikYRLq6fDg6q0icNGZiKDpOR1i5AACAPwAAgD8AqKg9rl+Zurgw7zrPpcA1mloCOyI5CroAAIA/AACAP5olurtSCPy5KlDCuaparjRqGi67jVoltAAAgD8AAIA/QDyYvrUfOj/6PRI+H4irvnrJk72dkcK8AAAAAAAAAABmOr+7DI6zP/yMk77XXka+HCWSO4LbpjwAAAAAAAAAAI0WRj7fuMQ8y68xOcXN8Desk1s+xnKGuAAAgD8AAIA/lmynvgE1PD+Axme+MZiMvkHmW741PIA9AAAAAAAAAADz1bm9e6KUugb6krtmFac4ZEjJubnTCjoAAIA/AACAP5qHarzDpbA/Ys2GvouVp754HZS7Hf7avQAAAAAAAAAAAALGvI96Wbr3uMY6AM6+NS208TqCEOq5AACAPwAAgD8mXQk+Cvkvu4D4oL3lu/08WGEOPVFVBr4AAIA/AACAP5SMBW51bXB5lIwFZHR5cGWUk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGJLEEsIhpSMAUOUdJRSlC4="}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVhAAAAAAAAACME251bXB5Ll9jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksQhZSMAUOUdJRSlC4="}, "_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:": "gAWV3AAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFm51bXB5Ll9jb3JlLm11bHRpYXJyYXmUjAZzY2FsYXKUk5SMBW51bXB5lIwFZHR5cGWUk5SMAmk4lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGJDCAQAAAAAAAAAlIaUUpSMBXN0YXJ0lGgIaA5DCAAAAAAAAAAAlIaUUpSMBl9zaGFwZZQpjAVkdHlwZZRoDowKX25wX3JhbmRvbZROdWIu", "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:": "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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-6.1.123+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sun Mar 30 16:01:29 UTC 2025", "Python": "3.11.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.6.0+cu124", "GPU Enabled": "True", "Numpy": "2.0.2", "Cloudpickle": "3.1.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}