GPU-Accelerated Robotic Simulation for Distributed Reinforcement Learning

Understand

Most Deep Reinforcement Learning (Deep RL) algorithms require a prohibitively large number of training samples for learning complex tasks.

• Many recent works on speeding up Deep RL have focused on distributed training and simulation.
• While distributed training is often done on the GPU, simulation is not.
• In this work, we propose using GPU-accelerated RL simulations as an alternative to CPU ones.