NSF award 2622695 · Arizona State University

Collaborative Research: SODA: Self-Organizing Decentralized Agents

Final report due

28 January 2030

in 1,198 days · The award ends on 30 September 2029.

GrantClerk is a private service. We are not NSF or any government agency.

Dates this award owes

NSF emails you about this too.

Decide about an extension2 Jun 2029in 958 days
award ending 2029-09-30 · Research.gov
This one is ours, not NSF’s.
Extension request16 Aug 2029in 1033 days
award ending 2029-09-30 · Research.gov
PAPPG 24-1: “at least 45 days prior to the end date”
No-cost extension notice20 Sep 2029in 1068 days
award ending 2029-09-30 · Research.gov
PAPPG 24-1: “at least ten calendar days prior to the end date”
Final report due28 Jan 2030in 1198 days
award ending 2029-09-30 · Research.gov
PAPPG 24-1: “no later than 120-days following the end date of the award”
Project outcomes report due28 Jan 2030in 1198 days
award ending 2029-09-30 · Research.gov
PAPPG 24-1: “no later than 120 days following the end date”
Award is closed out28 Jan 2030in 1198 days
award ending 2029-09-30 · Research.gov
PAPPG 24-1: “financially closed out 120 days after their expiration date”

Annual report dates come from the budget period on your award notice. That date is not public, so it is not shown here.

How we got this date

NSF lists this award's end date as 30 September 2029.
NSF rules say the final report is due no later than 120 days after that.
So the final report is due by 28 January 2030.

Read the rule on Research.gov

Get a note before each report date

Add this award to your desk. We email you before each date and keep the dates in one place.

Renews each year until you cancel. Cancel any time from your account.

Already a member? Sign in

Award card

Award number: 2622695
Period of support: 1 Oct 2026 – 30 Sep 2029
Amount: $150,000
Awardee: Arizona State University, Scottsdale, AZ
Program: CSCS: Circuits and Systems for
Directorate: ENG

Abstract

Artificial intelligence systems increasingly operate as groups of interacting agents that divide work, share information, use tools, and make decisions over many steps. However, most current multi-agent artificial intelligence systems still rely on a central controller to assign tasks and coordinate behavior, creating scalability bottlenecks, single points of failure, and barriers to collaboration when agents have…

Is this right?

We copy this from the public NSF award record. Your award notice and NSF always win. If a date looks wrong, check Research.gov.