DDPPO is a method for distributed reinforcement learning in resource-intensive simulated environments based on PPO. DD-PPO is distributed (uses multiple machines), decentralized (lacks a centralized server), and synchronous (no computation is ever stale), making it conceptually simple and easy to implement.

conda create -n rllib-ddppo python=3.10
conda activate rllib-ddppo
pip install -r requirements.txt
pip install -e '.[development]'

DDPPO Example