Gaming the Research: Reinforcement Learning Changing Data Evaluation Challenges

Advances in artificial intelligence, specifically reinforcement learning, are proving beneficial to accelerating the pace of data-intensive challenges. The methods used by researchers with RL are techniques often used in video games, and by applying gamification to scientific processes, RL agents can learn as they are used in experiments, in effect, leveling up their rates of discovery as they work. Researchers are using trained RL agents at NSLS-II to accelerate the analysis of data-heavy measurements.

Game on: Science Edition

UPTON, NY — Inspired by the mastery of artificial intelligence (AI) over games like Go and Super Mario, scientists at the National Synchrotron Light Source II (NSLS-II) trained an AI agent — an autonomous computational program that observes and acts — how to conduct research experiments at superhuman levels by using the same approach. The Brookhaven team published their findings in the journal Machine Learning: Science and Technology and implemented the AI agent as part of the research capabilities at NSLS-II.

FAU Researchers Receive Prestigious NSF CAREER Awards

Two researchers from FAU’s College of Engineering and Computer Science have received the coveted National Science Foundation (NSF) Early Career (CAREER) awards totaling more than $1 million. Xiangnan Zhong, Ph.D. and Zhen Ni, Ph.D., assistant professors in the Department of Computer and Electrical Engineering and Computer Science, received the NSF CAREER awards to drive the current artificial intelligence (AI) wave.