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README.md

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<details><summary><b>Version History</b> <i>[click to expand]</i></summary>
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<div>
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* 1.0.2 (Current version)
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Changes:
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* Fix bugs in SAC algorithm
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* 1.0.3 (Current version)
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Changes:
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* Fix bugs in SAC algorithm
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* 1.0.1
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```pip3 install -r requirements.txt```
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<details><summary><b>List of prerequisites.</b> <i>[click to expand]</i></summary>
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* tensorflow >= 2.0.0 or tensorflow-gpu >= 2.0.0a0
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* tensorlayer >= 2.0.1
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* tensorflow-probability
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<details><summary><b>Some notes on environment usage.</b> <i>[click to expand]</i></summary>
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* Make sure the name of environment matches the type of environment in the main script. The types of environments include: 'atari', 'box2d', 'classic_control', 'mujoco', 'robotics', 'dm_control', 'rlbench'.
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* When using the DeepMind Control Suite, install the [dm2gym](https://github.com/zuoxingdong/dm2gym) package with: `pip install dm2gym`
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<details><summary><b>4. Interactive reinforcement learning configuration.</b> <i>[click to expand]</i></summary>
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As shown in the interactive use case in Section of Usage, a jupyter notebook is provided for more intuitively configuring the whole process of deploying the learning process ([`rlzoo/interactive/main.ipynb`](https://github.com/tensorlayer/RLzoo/blob/master/rlzoo/interactive/main.ipynb))
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</details>

docs/conf.py

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author = 'Zihan Ding, Tianyang Yu, Yanhua Huang, Hongming Zhang, Hao Dong'
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# The full version, including alpha/beta/rc tags
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release = '1.0.2'
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release = '1.0.3'
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# -- General configuration ---------------------------------------------------

setup.py

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setup(
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name = "rlzoo",
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version = "0.0.1",
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version = "1.0.3",
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include_package_data=True,
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author='Zihan Ding, Tianyang Yu, Yanhua Huang, Hongming Zhang, Hao Dong',
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author_email='[email protected]',

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