NSF award 2542543 · Pennsylvania State Univ University Park

CAREER: Scaling Deep Reinforcement Learning for Societal-Scale Cyber-Physical Systems

Final report due

28 October 2031

in 1,836 days · The award ends on 30 June 2031.

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Decide about an extension2 Mar 2031in 1596 days
award ending 2031-06-30 · Research.gov
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Extension request16 May 2031in 1671 days
award ending 2031-06-30 · Research.gov
PAPPG 24-1: “at least 45 days prior to the end date”
No-cost extension notice20 Jun 2031in 1706 days
award ending 2031-06-30 · Research.gov
PAPPG 24-1: “at least ten calendar days prior to the end date”
Final report due28 Oct 2031in 1836 days
award ending 2031-06-30 · Research.gov
PAPPG 24-1: “no later than 120-days following the end date of the award”
Project outcomes report due28 Oct 2031in 1836 days
award ending 2031-06-30 · Research.gov
PAPPG 24-1: “no later than 120 days following the end date”
Award is closed out28 Oct 2031in 1836 days
award ending 2031-06-30 · Research.gov
PAPPG 24-1: “financially closed out 120 days after their expiration date”

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NSF lists this award's end date as 30 June 2031.
NSF rules say the final report is due no later than 120 days after that.
So the final report is due by 28 October 2031.

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Award card

Award number: 2542543
Period of support: 1 Jul 2026 – 30 Jun 2031
Amount: $685,588
Awardee: Pennsylvania State Univ University Park, University Park, PA
Program: CPS-Cyber-Physical Systems
Directorate: CSE

Abstract

This project will develop artificial intelligence techniques to improve the operation of large-scale infrastructure systems, such as smart transportation networks and electric power grids, which are essential to modern life. These complex systems, known as societal-scale cyber-physical systems, integrate physical infrastructure with thousands of sensors, computing devices, and actuators. Due to their scale and…

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