Open samlobel opened 1 year ago
Hi @samlobel and thank you for using sheeprl for your experiments! If you want we can start with a standard DDQN agent: you can have a look at our PPO implementations from this branch where we have the possibility to encode both images and vectors. We can start after the mentioned branch is merged, hopefully this week
@samlobel you can now try out directly the main branch
I am thinking of using sheeprl as the base for my RL experiments! My work usually builds off of DQN-type algorithms: in increasing level of complexity, off of DDQN, Rainbow, or R2D2. Having some of these implemented would make this library much more convenient for research IMO.
It's super cool that you have Dreamer and Plan2Explore implemented, but that's not a great starting point for RL research because of how complex and opinionated they are. It would be great to just have a simple DDQN baseline implemented! All the PPO and A2C stuff is great if you work in the online setting, but DQN type things would let us build things for batch training. In a perfect world it'd also have an implementation of something like R2D2 since that's a good SOTA-ish DQN upgrade.
Excited to start trying it out!