Rachel Fong — accepted AI-conference papers

2017

Domain randomization for transferring deep neural networks from simulation to the real world

Josh Tobin, Rachel Fong, Alex Ray, Jonas Schneider, Wojciech Zaremba, Pieter Abbeel

IROS 2017poster

Bridging the `reality gap' that separates simulated robotics from experiments on hardware could accelerate robotic research through improved data availability. This paper explores domain randomization, a simple technique for training models on simulated images that transfer to real images by randomi…

Cited by 3867 Source ↗Scholar ↗

2017

Hindsight Experience Replay

Marcin Andrychowicz, Filip Wolski, Alex Ray, Jonas Schneider, Rachel Fong, Peter Welinder +4

NeurIPS 2017poster

Dealing with sparse rewards is one of the biggest challenges in Reinforcement Learning (RL). We present a novel technique called Hindsight Experience Replay which allows sample-efficient learning from rewards which are sparse and binary and therefore avoid the need for complicated reward engineering…

Cited by 3290 Source ↗PDF ↗Scholar ↗