ahforoughi
commited on
Commit
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83e84b6
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Parent(s):
a1d2b57
Upload PPO LunarLander-v2-2m trained agent
Browse files- PPO-LunarLander-v2-2M.zip +3 -0
- PPO-LunarLander-v2-2M/_stable_baselines3_version +1 -0
- PPO-LunarLander-v2-2M/data +99 -0
- PPO-LunarLander-v2-2M/policy.optimizer.pth +3 -0
- PPO-LunarLander-v2-2M/policy.pth +3 -0
- PPO-LunarLander-v2-2M/pytorch_variables.pth +3 -0
- PPO-LunarLander-v2-2M/system_info.txt +9 -0
- README.md +1 -1
- config.json +1 -1
- replay.mp4 +0 -0
- results.json +1 -1
PPO-LunarLander-v2-2M.zip
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version https://git-lfs.github.com/spec/v1
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oid sha256:bc69a57a1a341e8246b86448ecb22d0de5a6030bf998b44d32a1c46f4894c8f6
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size 147962
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PPO-LunarLander-v2-2M/_stable_baselines3_version
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2.0.0a5
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PPO-LunarLander-v2-2M/data
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{
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"policy_class": {
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":type:": "<class 'abc.ABCMeta'>",
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"__module__": "stable_baselines3.common.policies",
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"__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 ",
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"__init__": "<function ActorCriticPolicy.__init__ at 0x7ce304adb880>",
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"_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7ce304adb910>",
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"reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7ce304adb9a0>",
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"forward": "<function ActorCriticPolicy.forward at 0x7ce304adbb50>",
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"extract_features": "<function ActorCriticPolicy.extract_features at 0x7ce304adbbe0>",
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"_predict": "<function ActorCriticPolicy._predict at 0x7ce304adbd00>",
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},
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- OS: Linux-6.1.58+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sat Nov 18 15:31:17 UTC 2023
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README.md
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type: LunarLander-v2
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type: LunarLander-v2
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replay.mp4
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results.json
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