I am quite familiar with traditional Machine Learning and Deep Learning (especially Computer Vision), I have been mainly using TensorFlow2/Keras and some Pytorch.

Recently, I am learning Deep Reinforcement Learning, after attempting to write some of the algorithms with TensorFlow2 + pure Python, I heard that there are higher-level libraries for DRL like TF-Agent and Dopamine. However, it seems like there are way too many of them and I cannot figure out which is best for me, considering each of them is better at certain fields/aspects. I am looking for a Python library that is mainly good at (by good at, I mean it provides sufficient features/functions/algorithms, relatively efficient implementations, and people are more likely to use it for the listed purposes):

Video Gameplays (for example, playing Atari games, I've heard that some are better at research, some are better at robotics, so that's why I have this preference listed)
TensorFlow2-based preferred (so I can build models or use functions from TensorFlow2)
Support Multi-Agent
Support Deep Learning Model running on GPU
Support Not just Simulations like Gym, but actual computer games
Have decent documentations

Any help and recommendations would be great! Thanks.

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