dqn-LunarLander-v2 / config.json
vumichien's picture
Upload DQN LunarLander-v2 trained agent
408ff0f verified
raw
history blame
13.6 kB
{"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 0x7c1552099000>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7c1552099090>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7c1552099120>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7c15520991b0>", "_build": "<function ActorCriticPolicy._build at 0x7c1552099240>", "forward": "<function ActorCriticPolicy.forward at 0x7c15520992d0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7c1552099360>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7c15520993f0>", "_predict": "<function ActorCriticPolicy._predict at 0x7c1552099480>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7c1552099510>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7c15520995a0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7c1552099630>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7c1552096180>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 16384, "_total_timesteps": 1000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1729519628671140045, "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:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAQAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -15.384, "_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": 4, "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:": "gAWVrQIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTAvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUjARmdW5jlEuEQwIEAZSMA3ZhbJSFlCl0lFKUfZQojAtfX3BhY2thZ2VfX5SMGHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbpSMCF9fbmFtZV9flIwec3RhYmxlX2Jhc2VsaW5lczMuY29tbW9uLnV0aWxzlIwIX19maWxlX1+UjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjEwL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUaACMEl9mdW5jdGlvbl9zZXRzdGF0ZZSTlGgffZR9lChoFowEZnVuY5SMDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgXjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz/JmZmZmZmahZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "system_info": {"OS": "Linux-6.1.85+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Thu Jun 27 21:05:47 UTC 2024", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.4.1+cu121", "GPU Enabled": "True", "Numpy": "1.26.4", "Cloudpickle": "3.1.0", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}