crossrefFrontiers in Robotics and AI2026-07-01
Exploring deep reinforcement learning acceleration by superscaling data augmentation via branched fractal symmetries
Ryan Vander Stelt, Cleiver Ruiz-Martinez, Caeden Rosen, Blake Hull, Juan Rojas
Learning deep reinforcement learning (DRL) policies directly in physical robots remains bottlenecked by slow wall-clock training times. We present preliminary research on Branched Euclidean Group Fractal Symmetries , a trajectory-level augmentation framework that super-scales gro…