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ars-MountainCarContinuous-v0-522674030

Reinforcement Learning
stable-baselines3
MountainCarContinuous-v0
deep-reinforcement-learning
Eval Results
Model card Files Community
ars-MountainCarContinuous-v0-522674030
File size: 13,050 Bytes 
cab8362
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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{
    "policy_class": {
        ":type:": "<class 'abc.ABCMeta'>",
        ":serialized:": "gAWVKgAAAAAAAACMGHNiM19jb250cmliLmFycy5wb2xpY2llc5SMCUFSU1BvbGljeZSTlC4=",
        "__module__": "sb3_contrib.ars.policies",
        "__doc__": "\n    Policy network for ARS.\n\n    :param observation_space: The observation space of the environment\n    :param action_space: The action space of the environment\n    :param net_arch: Network architecture, defaults to a 2 layers MLP with 64 hidden nodes.\n    :param activation_fn: Activation function\n    :param with_bias: If set to False, the layers will not learn an additive bias\n    :param squash_output: For continuous actions, whether the output is squashed\n        or not using a ``tanh()`` function. If not squashed with tanh the output will instead be clipped.\n    ",
        "__init__": "<function ARSPolicy.__init__ at 0x7fb359519280>",
        "_get_constructor_parameters": "<function ARSPolicy._get_constructor_parameters at 0x7fb359519310>",
        "forward": "<function ARSPolicy.forward at 0x7fb3595193a0>",
        "_predict": "<function ARSPolicy._predict at 0x7fb359519430>",
        "__abstractmethods__": "frozenset()",
        "_abc_impl": "<_abc._abc_data object at 0x7fb35951e080>"
    },
    "verbose": 1,
    "policy_kwargs": {
        "net_arch": [
            16
        ]
    },
    "observation_space": {
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        "dtype": "float32",
        "_shape": [
            2
        ],
        "low": "[-1.2  -0.07]",
        "high": "[0.6  0.07]",
        "bounded_below": "[ True  True]",
        "bounded_above": "[ True  True]",
        "_np_random": null
    },
    "action_space": {
        ":type:": "<class 'gym.spaces.box.Box'>",
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        "bounded_above": "[ True]",
        "_np_random": "RandomState(MT19937)"
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    "_total_timesteps": 500000,
    "_num_timesteps_at_start": 0,
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