My old self passionately said:
This repository is a comprehensive list of all of my state-of-the-art Deep Reinforcement Learning implementations and I have been fortunate to get the chance to write their code form scratch based on my understanding about each and every one of them.
Each directory refers you to the corresponding repository that the algorithm has been put together. I would be more than happy to have your thoughts in the issues section of this repository or on the corresponding algorithm's repo.
After reading Empirical Design in Reinforcement Learning, I say:
Of all issues that the repos possess, they show some results only for a single seed! 😲 So don't take the repos very seriously unless you test them for a handful number of seeds!