Ashley1902's picture
Lunar_Lander 5e6 Steps, mean reward: 280.57 +/- 13.54
7bd6edb
{
"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 sde_net_arch: Network architecture for extracting features\n when using gSDE. If None, the latent features from the policy will be used.\n Pass an empty list to use the states as features.\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 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 0x7f128374d790>",
"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f128374d820>",
"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f128374d8b0>",
"_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f128374d940>",
"_build": "<function ActorCriticPolicy._build at 0x7f128374d9d0>",
"forward": "<function ActorCriticPolicy.forward at 0x7f128374da60>",
"_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f128374daf0>",
"_predict": "<function ActorCriticPolicy._predict at 0x7f128374db80>",
"evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f128374dc10>",
"get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f128374dca0>",
"predict_values": "<function ActorCriticPolicy.predict_values at 0x7f128374dd30>",
"__abstractmethods__": "frozenset()",
"_abc_impl": "<_abc_data object at 0x7f128374a300>"
},
"verbose": 1,
"policy_kwargs": {},
"observation_space": {
":type:": "<class 'gym.spaces.box.Box'>",
":serialized:": "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",
"dtype": "float32",
"_shape": [
8
],
"low": "[-inf -inf -inf -inf -inf -inf -inf -inf]",
"high": "[inf inf inf inf inf inf inf inf]",
"bounded_below": "[False False False False False False False False]",
"bounded_above": "[False False False False False False False False]",
"_np_random": null
},
"action_space": {
":type:": "<class 'gym.spaces.discrete.Discrete'>",
":serialized:": "gAWVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu",
"n": 4,
"_shape": [],
"dtype": "int64",
"_np_random": null
},
"n_envs": 16,
"num_timesteps": 5013504,
"_total_timesteps": 5000000,
"_num_timesteps_at_start": 0,
"seed": null,
"action_noise": null,
"start_time": 1670512689795463040,
"learning_rate": 0.0003,
"tensorboard_log": null,
"lr_schedule": {
":type:": "<class 'function'>",
":serialized:": "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"
},
"_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": -0.0027007999999999477,
"ep_info_buffer": {
":type:": "<class 'collections.deque'>",
":serialized:": "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"
},
"ep_success_buffer": {
":type:": "<class 'collections.deque'>",
":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
},
"_n_updates": 1530,
"n_steps": 2048,
"gamma": 0.99,
"gae_lambda": 0.95,
"ent_coef": 0.0,
"vf_coef": 0.5,
"max_grad_norm": 0.5,
"batch_size": 64,
"n_epochs": 10,
"clip_range": {
":type:": "<class 'function'>",
":serialized:": "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"
},
"clip_range_vf": null,
"normalize_advantage": true,
"target_kl": null
}