Support for MiniWorld (3D indoor environment)?

Hi Lucas,

I’ve been working on my 3D indoor environment. It’s still very basic, but it works, and I just made the repository public: https://github.com/maximecb/gym-miniworld

I’ve tried to adjust your pytorch-a2c-ppo code to work with MiniWorld, but ran into issues. One is that MiniWorld produces observations which are not dictionary-based, and it was awkward to support this (the obs are just 60x80x3 RGB arrays). The other is that I only got something like 16 frames per second while training with 16 processes, and I have no idea why.

Would you have time to take a look? It would be great if it could work with your RL code out of the box. Right now I’m using my own fork of ikostrikov’s, but there are multiple other issues with that code, one of which is that the performance when visualizing trained agents doesn’t match the performance reported while training.

[maximecb]

Yes, with this command to launch training:

python3 main.py --algo ppo --num-frames 5000000 --num-processes 16 --num-steps 80 --lr 0.00005 --env-name MiniWorld-Hallway-v0

[maximecb]

With multiple processes or with just 1? I usually train with 16+.