Spinning Up in Deep RL
This developed-and-maintained package is a good approach towards furthering RL development; as the writeups state, the biggest problem in RL is subtle bugs from an implementation which don't cause an error but tank learning performance. (+ loggers/utils to help debug things)<p>Granted, a lot of RL thought pieces/examples on places like Medium.com take an existing RL implementation without many tweaks, run it on a new task, and see what happens. A better  RL library might make this workflow more prevalent; hence why it's very important for researchers to make their pipelines transparent.