NSF award 2529645 · University of California-Berkeley

CPS-Small: Provable Enforcement of Hard Constraints in Reinforcement Learning-Based Controllers for Safety-Critical CPS

Final report due

30 April 2029

in 925 days · The award ends on 31 December 2028.

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award ending 2028-12-31 · Research.gov
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Extension request16 Nov 2028in 760 days
award ending 2028-12-31 · Research.gov
PAPPG 24-1: “at least 45 days prior to the end date”
No-cost extension notice21 Dec 2028in 795 days
award ending 2028-12-31 · Research.gov
PAPPG 24-1: “at least ten calendar days prior to the end date”
Final report due30 Apr 2029in 925 days
award ending 2028-12-31 · Research.gov
PAPPG 24-1: “no later than 120-days following the end date of the award”
Project outcomes report due30 Apr 2029in 925 days
award ending 2028-12-31 · Research.gov
PAPPG 24-1: “no later than 120 days following the end date”
Award is closed out30 Apr 2029in 925 days
award ending 2028-12-31 · 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 31 December 2028.
NSF rules say the final report is due no later than 120 days after that.
So the final report is due by 30 April 2029.

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Award card

Award number: 2529645
Period of support: 1 Jan 2026 – 31 Dec 2028
Amount: $600,000
Awardee: University of California-Berkeley, Berkeley, CA
Program: CPS-Cyber-Physical Systems
Directorate: CSE

Abstract

As autonomous systems like self-driving cars and delivery robots become more common, making sure that they operate safely is critical. These systems often learn how to act using reinforcement learning (RL). While powerful, RL methods typically do not guarantee safety, which limits their use in the real world. A common approach towards capturing safety in RL is ensuring the satisfaction of safety constraints.…

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