Where to start learning model/policy customization?

RLlib
1

I am interested in learning how to customize policies/models by reading DQN’s code (because the official RLlib documentation is really hard to follow). However, I feel pretty confused when reading it.

Where I should start to learn/read?
Is there any clearer tutorial relating to policies/models customization?
Should I have a strong TensorFlow or PyTorch background?

2

Probably a good start is the tutorial from @sven1977 : Anyscale - Hands-on Reinforcement Learning with Ray’s RLlib

A next step could be to start with some examples: ray/rllib/examples at master · ray-project/ray · GitHub

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