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I was recommended to ask here after I posted on stack overflow wrongly.

I was wondering if anyone had any recommended readings on layers used in neural networks for reinforcement learning?

I've been coding with RL for maybe a month now (using Matlab/Simulink - wanting to get started with Python as well) and I have managed to make one of my projects work however I was mainly modifying code elsewhere and adding new functions to it so I never understood how the different kind of layers worked.

I understand that depending on the problem and agent used this will vary so any sources on how to understand this better would be really appreciated!

Thanks in advance :)

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