Looking for simpler RL baselines? Checkout the DQN examples implemented from scratch using PyTorch.
The following baselines provide a starting point to develop advanced reinforcement learning solutions. They use the RLlib framework, which makes it easy to scale up training to larger machines or even to clusters of machines.
Follow the getting started guide to setup and start training using the RLlib baselines.
The RLlib documentation provides ample information about the standard methods such as Ape-X and PPO. The documentation below gives more details about the methods, custom observations and other approaches that have been developed specifically for Flatland.