rlpyt: A Research Code Base for Deep Reinforcement Learning in PyTorch

Understand

Since the recent advent of deep reinforcement learning for game play and simulated robotic control, a multitude of new algorithms have flourished.

• Most are model-free algorithms which can be categorized into three families: deep Q-learning, policy gradients, and Q-value policy gradients.
• These have developed along separate lines of research, such that few, if any, code bases incorporate all three kinds.
• Yet these algorithms share a great depth of common deep reinforcement learning machinery.