{
    "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 0x7f6584250d30>",
        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f6584250dc0>",
        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f6584250e50>",
        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f6584250ee0>",
        "_build": "<function ActorCriticPolicy._build at 0x7f6584250f70>",
        "forward": "<function ActorCriticPolicy.forward at 0x7f6584251040>",
        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f65842510d0>",
        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f6584251160>",
        "_predict": "<function ActorCriticPolicy._predict at 0x7f65842511f0>",
        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f6584251280>",
        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f6584251310>",
        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f65842513a0>",
        "__abstractmethods__": "frozenset()",
        "_abc_impl": "<_abc._abc_data object at 0x7f6584252380>"
    },
    "verbose": 1,
    "policy_kwargs": {},
    "observation_space": {
        ":type:": "<class 'gym.spaces.box.Box'>",
        ":serialized:": "gAWVYwEAAAAAAACMDmd5bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lGgFk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMBl9zaGFwZZRLAoWUjANsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWCAAAAAAAAACamZm/KVyPvZRoCksChZSMAUOUdJRSlIwEaGlnaJRoEiiWCAAAAAAAAACamRk/KVyPPZRoCksChZRoFXSUUpSMDWJvdW5kZWRfYmVsb3eUaBIolgIAAAAAAAAAAQGUaAeMAmIxlImIh5RSlChLA4wBfJROTk5K/////0r/////SwB0lGJLAoWUaBV0lFKUjA1ib3VuZGVkX2Fib3ZllGgSKJYCAAAAAAAAAAEBlGghSwKFlGgVdJRSlIwKX25wX3JhbmRvbZROdWIu",
        "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'>",
        ":serialized:": "gAWVBAwAAAAAAACMDmd5bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lGgFk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMBl9zaGFwZZRLAYWUjANsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWBAAAAAAAAAAAAIC/lGgKSwGFlIwBQ5R0lFKUjARoaWdolGgSKJYEAAAAAAAAAAAAgD+UaApLAYWUaBV0lFKUjA1ib3VuZGVkX2JlbG93lGgSKJYBAAAAAAAAAAGUaAeMAmIxlImIh5RSlChLA4wBfJROTk5K/////0r/////SwB0lGJLAYWUaBV0lFKUjA1ib3VuZGVkX2Fib3ZllGgSKJYBAAAAAAAAAAGUaCFLAYWUaBV0lFKUjApfbnBfcmFuZG9tlIwUbnVtcHkucmFuZG9tLl9waWNrbGWUjBJfX3JhbmRvbXN0YXRlX2N0b3KUk5SMB01UMTk5MzeUaC2MFF9fYml0X2dlbmVyYXRvcl9jdG9ylJOUhpRSlH2UKIwNYml0X2dlbmVyYXRvcpSMB01UMTk5MzeUjAVzdGF0ZZR9lCiMA2tleZRoEiiWwAkAAAAAAAAAAACAU8KznIcDtZNy7Ktb6Oay8s+2gdrVBu9hoTFNoGu1zNkT5hifdJx5L8ilG4DEeQFJng9D5F3gGJOSE1XM1EopZNIIlb400J5EcnoD8K2/CnObez7pYLEG2nUDRQtufdYWausENGaDt/P1pS9p70JjQ7Vc98J3UsxGRDctCIlu0I6ud/sYtoBPe575TzLsEti5jl6FqRnKrj12LWcrQoCexe7HH/UiAV1LzyQPzBlSZERXmHCdCvUSF7XpWt47xP9BzzqxX7aH3TPYWImqos1/ez/JlLdsD0MfMZl9G2CQq7cHHRlM3sj7jroA9c+pGt4l/iAGpRb80HbjwU71ykPTAVp531BXrc2qmIU6z9Fh4TAPx7fZ1kVF+L1Irlou+4Ckky7Ys59nB7KkciTI+N5jlb62ybZt0+ZWgIA6LKLvdx/mTQtB4k1aplT/C7L9/ybKCFn2quN/7YlIkxoH1U0xdabG6rgOrR+SHMmvUwvtKB+19Ibb07mSgVQyjNAvnyADPJf3pkxylZtn7f/OVpWEaWfl6BcLwy0grrEgUK+H+8P8XWMuBginXgwzn3sy4+ZOlr45op6TtuqX0Knz/SySGDlBIK8JqKObzB6fGt+ovJHEM8KlL4veKwkLkuuMWBaex3FBdWskry5qhslxMgnk2thh8DaXmAfbuI8j0SqHMW1kleITi9ekfXx/eSi5hX1GjA/M62Zixuay1H8zH9VjsTRcGacyJ0vh1hNReDFoNsXFbLfLqaIvbLDQjY7T289ZXsupvAxu2GVTbqWst+ckPPzwH7vLikULC+weAKwxarqm+ugAXgyz774meHOsvQYuu18nvrrunjZWDvwaKuYohEwUfSnpotE9XhX99yUTc8sGPQidTfXkzm/t8MWP8it4l4VSEgDLn8GW8t2DAh8EwFa/KOGoZEGjYqZ2IMA70E+F2LqgaZlQLFMONTIx3yuN5F2e1MT4v2wdBRK9R+lGMpxIiNldyOwwxLDBTRDMhd7APidmDwQBnvaIecKFa95btwHkRBEUT5g++/I0DDg685EX4OMO2YtTPqM3PQluS4puEhAQRVukNGSh4gYDgcBPKZl4ThNf+G+E7El9fmWJcP39Sifw6Mn+GEisM1RhHY05XZHUv5W4r8kD2jSLMY+IIL2+LtQrW7it7y28+sEicLoEfYOky9ZJF6l0fR+sXEawf+REH9LvtRJ4yzfxr7KisNpr1axv1ae5CDXS+XTzuOG/BJnHvt8arnY1XWH9SdkCOeok6MI8GBCtjTCxJ5JbpI5J0i0A66mJaRW9LMfP6Cil3/cVRQ9uN2KTtV3o7rJwY4XCnj7DJmqrUwofDDl7Ek0PoN7w0Hh8YHOy8qhPw7V8ALdjZn7eYtjCQIldQvHbM1I73RtCLQvQGFMXUCJ022pGRqTvZX5XWSizqbgX6TJmI6LDF9wcpYealB7cDwelfqdpzHRmyjRbIX9b+w4uj//aDRgP2SgiOAq/D/9/0SbgK/E0FQyclhNVAkbKwXhAxKGczpvJow0mFFUAt/5fT5KAsmQTAt8p0FsrGMDTfk4RzZgqZSm+ihVRS371Tx3twpGA1goo/AIfJh8slJC3hkR1OGCN7LAPGCwbM9rHlKSU4uuhJiff196h9q1kPMld6989MfKLVkvCl7ofCRurPUW46ceJKE951sQD1v8cK0HK1JmuBTCXAelCUCIFNLGk3tMXNVmuuFF3o3xb4V4T1IAYIfBdyEVHhIIZOE/JEY79daQw8njYEtQ6YwZ6kNCBYfrjq2OglITcRdwDmINL42ro6HnbWgLZQ8Ce/EiPVBtWHwhvGUHK1FNONzRzXgT1zKEg+WAigeuK4QVIxdITM4YvUyYvpQJuJd+xGD1no7BYIKXdV4aDlsRnWSMmS+zTyTvC0+TgBMCNpMvdChjaB/XTrMVsm0vgPmCYswn067MTYWfm5oCqqmNciqoRfFL2O2mxFT1VMcKDrxHBdBUhSG5UmAerx86KAEytbsCbn6OOj8Y02VwVynzXd0WJfLioeGMZISM1eneWfTc1mQ6CpdDxJqUmU86/KsBL3Bb0S2NAqFysFJZKxDwLej8xz+xH8IxEHzlkiiNH+2IIq0663FAwi6wg6dgcryDqQ+lNDwn898nylrcYShigDrtrFBNezKx3ZjpkPCnPUeQB4hJUrYCUJy5CyytC/x1UsByKez/aSNEWnlWnzYdJf2PoKL0YfmaR3KpXzi9ax3BHPgk1cdmgdVkqevFJ0DUdTBFQj/mhaKqcaT0rKJLgy/11AhWW4nX7+kAdgR0b1iAseI0TbMDtohBuqqUZfqMfUKsdI8v2aeUd0+IqOjPBFe7TZRC7OUYmf789SRTpw9gst4tzx7tLap8JnFt2keKhqd3vBgqpvlsxvx0DcPC+bo/qIldKiAn5D7TPjeWLzJ1gmpk1mVKOyWOv/ZzlRTfe8yEsMsRcgdPxbOuxLjlOwo1uFh9NjHoOz/xbnI62I49ZzT59GUCNtAL74UqjlRoyXZ5ELEjhTn+F5fYfEkY2TnSsgKO4Wwb/xD41S4mBL7LcUyF76ybV7Yx0L6V2QGoSfyhHFqMQJs/haLPPW18mWJb/UDl90ZN9TEzcdXvZsmCeqzCagC6YDHp3fop+5nAQSnT/Byt2j7z+6cnl/aZh6oKs5xrEMmuzpLFbXNVof9hNmX5E0DQ2M8uBqqeW95p6z8ySnOxURAO28oYWsbVyeYaNlWLZrOtIMZDRjjbecSSwMLlrBhw4mZVht4DgOQxI1+P7sPHZLMf89U+5ctf1rD0r1AXgyXjzOxKvCxWMhrz6Ah19+zal/bAIpw+0V7Pq85PRQO4UeScmMwODR8jcOfILuMmo7xXhemY/JqtOncklEaGapMeGlkiefvQkx9L5EWvLn6stI4zRP4pZXx9iOz17IKJmKOVHgCIAOiheb0bwkjNkItlfYO3LzeLLPuBDNLFg7tQu5NPWy28a4nBsE/gsyEteRvF2ECYFIOJg06dzc77IWw7o+z1Q5APxLg9uvyFniYWNuJyk7rflLCmYcg1gN657CWff8YfPr0ukKOamco94X1nFdyroxHiQlRXaP91DOqMueI1pCasyRQt0jtbWwxdEVyzP3GzUZXBWqa0xXCzwe29cxg2aiwKuuAAVfaCE/Pt1cJXq8wvliF81sMDPMbowd9+uyWuExq/e+2W3wWeV3hVofoiEySjBrJPWVJW9++UocJbC0ppNw5mtHktkZqUk6kVtUgVQ4Cj4udj/bluZzcqWjIvOCJO52M+xcQY808Ei8T/lwwS9TguuzQ3e0KR7hptgNcX1/XhCvAuUaAeMAnU0lImIh5RSlChLA2gLTk5OSv////9K/////0sAdJRiTXAChZRoFXSUUpSMA3Bvc5RNcAJ1jAloYXNfZ2F1c3OUSwCMBWdhdXNzlEcAAAAAAAAAAHVidWIu",
        "dtype": "float32",
        "_shape": [
            1
        ],
        "low": "[-1.]",
        "high": "[1.]",
        "bounded_below": "[ True]",
        "bounded_above": "[ True]",
        "_np_random": "RandomState(MT19937)"
    },
    "n_envs": 1,
    "num_timesteps": 53248,
    "_total_timesteps": 50000,
    "_num_timesteps_at_start": 0,
    "seed": 0,
    "action_noise": null,
    "start_time": 1670945649911223806,
    "learning_rate": 0.001,
    "tensorboard_log": "runs/MountainCarContinuous-v0__trpo__2747342494__1670945647/MountainCarContinuous-v0",
    "lr_schedule": {
        ":type:": "<class 'function'>",
        ":serialized:": "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"
    },
    "_last_obs": null,
    "_last_episode_starts": {
        ":type:": "<class 'numpy.ndarray'>",
        ":serialized:": "gAWVdQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYCAAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksChZSMAUOUdJRSlC4="
    },
    "_last_original_obs": {
        ":type:": "<class 'numpy.ndarray'>",
        ":serialized:": "gAWVhQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAJq9/r4AAAAAcbYHvwAAAACUjAVudW1weZSMBWR0eXBllJOUjAJmNJSJiIeUUpQoSwOMATyUTk5OSv////9K/////0sAdJRiSwJLAoaUjAFDlHSUUpQu"
    },
    "_episode_num": 0,
    "use_sde": true,
    "sde_sample_freq": 4,
    "_current_progress_remaining": -0.0649599999999999,
    "ep_info_buffer": {
        ":type:": "<class 'collections.deque'>",
        ":serialized:": "gAWV4AsAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpRHQFX2pMYdhiOMAWyUS5iMAXSUR0A5MnW8RL9NdX2UKGgGR0BVvqwljVhDaAdLpWgIR0A5tMtbs4T9dX2UKGgGR0BVoQu/UONHaAdLoGgIR0A5wqbz9S/CdX2UKGgGR0BVTH84xUNsaAdLxWgIR0A54ViF0xM4dX2UKGgGR0BWAF7D2rXEaAdLkGgIR0A541KoQ4CIdX2UKGgGR0BXTAXEZR8/aAdLVmgIR0A59LpA2Q4kdX2UKGgGR0BVxWU4aP0aaAdLlGgIR0A6BLronrprdX2UKGgGR0BXcS0jTrmhaAdLUWgIR0A6BvkBCD28dX2UKGgGR0BXWV4HHFP0aAdLTWgIR0A6GEnb7CSBdX2UKGgGR0BVzN43WFviaAdLmGgIR0A6Jv6CUX54dX2UKGgGR0BW4Yi9qUNbaAdLXmgIR0A6LgDA8B+4dX2UKGgGR0BXjpksjFAFaAdLTGgIR0A6Oi3G4qgAdX2UKGgGR0BW/QIt16mgaAdLWWgIR0A6RNKyv9tNdX2UKGgGR0BXGfQnhKlIaAdLWmgIR0A6W8JUo8ZDdX2UKGgGR0BWIzvE0iyIaAdLkGgIR0A6Xu8K5TZQdX2UKGgGR0BXXhWLgn+iaAdLXmgIR0A6c7JW/8EWdX2UKGgGR0BXIUPUaybAaAdLVGgIR0A6iS/CZWq+dX2UKGgGR0BV9vnwG4ZuaAdLr2gIR0A6i1Iy0rsjdX2UKGgGR0BXfzIzWPLgaAdLTmgIR0A6nyM1jy4GdX2UKGgGR0BXS6xkd3jdaAdLVmgIR0A6nvgWJrLydX2UKGgGR0BW8njU/fO2aAdLZmgIR0A6uSBK+SKWdX2UKGgGR0BV+mPYFqzraAdLmWgIR0A6xe6I3zczdX2UKGgGR0BXNLx3FDOUaAdLUmgIR0A6zdXko4MndX2UKGgGR0BXbvzBhx5taAdLR2gIR0A6191U2kzodX2UKGgGR0BVmdCzC1qnaAdLmGgIR0A69GwA2hqTdX2UKGgGR0BV9ECmuTzNaAdLn2gIR0A7AE25xzaLdX2UKGgGR0BW2sTnJT2naAdLcGgIR0A7EPppvgm7dX2UKGgGR0BU5JSm65G0aAdLwmgIR0A7M5HVf/m1dX2UKGgGR0BWVfUaya/iaAdLlWgIR0A7OThYNiH7dX2UKGgGR0BXV2G7BfrsaAdLbWgIR0A7UbzshPj5dX2UKGgGR0BWJf3i704BaAdLmWgIR0A7Y5d4VymzdX2UKGgGR0BW7s8La24NaAdLYmgIR0A7bRnOB19wdX2UKGgGR0BXZm/BWPtEaAdLS2gIR0A7gefZmI0qdX2UKGgGR0BVk7qyGBWgaAdLo2gIR0A7kUF0PpY+dX2UKGgGR0BVC4vzvqkeaAdLs2gIR0A8LbEP1+RYdX2UKGgGR0BWgdLpRoAXaAdLhGgIR0A8L9Aood+5dX2UKGgGR0BV4ASWZ7XyaAdLkWgIR0A8VhnrY5DJdX2UKGgGR0BVxP0qYqoZaAdLkGgIR0A8WAAyVObidX2UKGgGR0BVgzkMkQf7aAdLr2gIR0A8hw7kn1FpdX2UKGgGR0BUxcejmCAdaAdL72gIR0A8msnAqNIcdX2UKGgGR0BXWS2lVLi/aAdLR2gIR0A8ri+cpb2UdX2UKGgGR0BVrUvCdjG2aAdLnGgIR0A8shr30wrUdX2UKGgGR0BXKyXUpd8iaAdLVWgIR0A8yacqe9SNdX2UKGgGR0BWQPtY0VJuaAdLi2gIR0A81LronrprdX2UKGgGR0BXWrSy+pOvaAdLVGgIR0A84Pwd8zAOdX2UKGgGR0BXWKLKmsNlaAdLTGgIR0A86gxrSE13dX2UKGgGR0BXdUEovzvraAdLS2gIR0A8/syBTXJ6dX2UKGgGR0BV3o+B6KLsaAdLomgIR0A9DhLXcxj8dX2UKGgGR0BXJdd/rjYJaAdLZmgIR0A9Gw7DEWIodX2UKGgGR0BWV0GqxTsIaAdLhmgIR0A9Myz5XU6QdX2UKGgGR0BV7jefqX4TaAdLq2gIR0A9SpMHryDqdX2UKGgGR0BWKxJVbRnfaAdLj2gIR0A9WsYVIqb0dX2UKGgGR0BXKsFhXr+paAdLU2gIR0A9YUJOWSlndX2UKGgGR0BXekRBeHBUaAdLQ2gIR0A9c4593KSxdX2UKGgGR0BWbtaMaS9vaAdLimgIR0A9gJYT0xubdX2UKGgGR0BWHxcRlHz6aAdLkWgIR0A9m3Dej2zwdX2UKGgGR0BW9FvAGjbjaAdLfmgIR0A9o4H5aePJdX2UKGgGR0BXAmz4UN8WaAdLamgIR0A9uUaQ3gk1dX2UKGgGR0BWZgEMb3oLaAdLfWgIR0A9xpcX3xnWdX2UKGgGR0BXa3+ZPVNIaAdLTGgIR0A9zqB3A2ycdX2UKGgGR0BWZseKbaysaAdLiGgIR0A97ITGo73gdX2UKGgGR0BVuT0+TvAoaAdLjGgIR0A99Z7ojfNzdX2UKGgGR0BXRNITXarWaAdLU2gIR0A+A7KJVKf4dX2UKGgGR0BXIhtcfNiZaAdLUGgIR0A+C7fpD/lydX2UKGgGR0BVmMuOCGvfaAdLpGgIR0A+MY3Ns3yadX2UKGgGR0BV14IF/x2CaAdLp2gIR0A+OsWfseGPdX2UKGgGR0BWGKP0Zm7KaAdLk2gIR0A+0sC1Z1V6dX2UKGgGR0BVPULtu1neaAdLr2gIR0A+43225QP7dX2UKGgGR0BXYhwhnrY5aAdLVmgIR0A+6radtl7MdX2UKGgGR0BVpWiHqNZNaAdLnmgIR0A/DzImw7kodX2UKGgGR0BVwrMcIZ62aAdLkmgIR0A/Eslsxfv4dX2UKGgGR0BWJbtzCDVZaAdLiWgIR0A/NUT+NtIkdX2UKGgGR0BU/NbgTAWSaAdLwWgIR0A/ftEofCAMdX2UKGgGR0BXag8jiXIEaAdLT2gIR0A/gXOGCZnddX2UKGgGR0BXg0zO5avBaAdLSmgIR0A/kvWYnfEXdX2UKGgGR0BW1GaDwpfAaAdLbWgIR0A/nygwoLG8dX2UKGgGR0BXUJtix3V1aAdLR2gIR0A/sp2U0Nz9dX2UKGgGR0BVPutW+49YaAdLrWgIR0A/wmmLtNSJdX2UKGgGR0BXOhrJr+HaaAdLUWgIR0A/2VgQYk3TdX2UKGgGR0BVsaz7di2EaAdLrWgIR0A/4rKeTV2BdX2UKGgGR0BWKuNHYpUhaAdLgGgIR0A//AKOT7l8dX2UKGgGR0BV29+9alk6aAdLkmgIR0BABUMPSUkfdX2UKGgGR0BXTFlCkXUIaAdLVGgIR0BACYPGyX2NdX2UKGgGR0BWkXZoPCl8aAdLc2gIR0BAGISlFc6edX2UKGgGR0BVmm6kIomYaAdLmGgIR0BAGUONHYpVdX2UKGgGR0BXUE2LpA2RaAdLUWgIR0BAI47A+IM0dX2UKGgGR0BXNclolD4QaAdLWWgIR0BAI91uBMBZdX2UKGgGR0BW/GpEQXhwaAdLVGgIR0BALnzxwyZbdX2UKGgGR0BV7bUkOZssaAdLkGgIR0BANdAood+5dX2UKGgGR0BXXXZsbedkaAdLVWgIR0BAOWRzRx95dX2UKGgGR0BWpcMy8BdVaAdLgGgIR0BASWuX/o7ndX2UKGgGR0BVe2u9vjwQaAdLq2gIR0BAS349HMEBdX2UKGgGR0BVpniNsFdLaAdLo2gIR0BAXhJZntfHdX2UKGgGR0BUw4/7iyY5aAdL4mgIR0BAaAVXV9WqdX2UKGgGR0BXMGJJoTPCaAdLWmgIR0BAaXZ5AyEddX2UKGgGR0BXXl4X40uUaAdLSmgIR0BAcW56MR6GdX2UKGgGR0BXMpZ8rqdIaAdLWmgIR0BAdNPP9kz5dX2UKGgGR0BXILpV0cOtaAdLWWgIR0BAfKMFUyYYdX2UKGgGR0BXOeTibUgCaAdLUWgIR0BAhuDBdld1dX2UKGgGR0BWJ6ya/h2oaAdLl2gIR0BAh+2VmjCYdWUu"
    },
    "ep_success_buffer": {
        ":type:": "<class 'collections.deque'>",
        ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
    },
    "_n_updates": 13,
    "n_steps": 2048,
    "gamma": 0.99,
    "gae_lambda": 0.95,
    "ent_coef": 0.0,
    "vf_coef": 0.0,
    "max_grad_norm": 0.0,
    "normalize_advantage": true,
    "batch_size": 128,
    "cg_max_steps": 15,
    "cg_damping": 0.1,
    "line_search_shrinking_factor": 0.8,
    "line_search_max_iter": 10,
    "target_kl": 0.01,
    "n_critic_updates": 10,
    "sub_sampling_factor": 1
}