Reinforcement Learning and Kullback-Leibler Stochastic Optimal Control for Complex Networks

Principal Investigator: Sean Meyn

Sponsor: NSF

Start Date: September 15, 2019

End Date: August 31, 2022

Amount: $380,000

Abstract

Prof Meyn is developing new approaches to reinforcement learning (RL) and distributed control with wide-ranging applications.  This project concerns the development of this theory, and its application to reliable control and resource allocation for demand dispatch (an alternative to demand response for smart grid applications).

More Information: https://nsf.gov/awardsearch/showAward?AWD_ID=1935389&HistoricalAwards=false