NYU & Stanford’s GPUDrive: Achieving Over 1 Million Steps per Second in Multi-Agent Driving Simulations
A research team presents GPUDrive, a GPU-accelerated multi-agent simulator built on the Madrona Game Engine, which is capable of generating over a million experience steps per second, making it a game-changer for applying sample-inefficient yet powerful reinforcement learning algorithms to multi-agent planner design.
