Hackable PyTorch RL library with distributional algorithms (D4PG, DSAC, DPPO)

I published a paper on distributional RL for legged locomotion a while back and recently resurfaced and cleaned up the code into a standalone repo: https://github.com/e3ntity/e3rl

Here’s a DPPO policy trained with this library running on a real robot: https://sites.google.com/leggedrobotics.com/risk-aware-locomotion

The library is based on rsl_rl but contains readable PyTorch implementations of the most popular continuous control algorithms (PPO, SAC, TD3, DDPG), plus their distributional counterparts DPPO, DSAC, D4PG.

Runs on CUDA, Apple Silicon, or CPU. pip install -e . and python examples/example.py trains a policy on gym out of the box.