# CAREER: Identifying and Exploiting Multi-Agent Symmetries

> **NSF 01002324DB NSF RESEARCH & RELATED ACTIVIT** · Worcester Polytechnic Institute (MA) · $535,346

## Abstract

It is widely believed by scientists that our universe follows certain symmetry patterns and principles, which lead to profound implications such as conservation laws. Artificial intelligence (AI) can and has already benefited tremendously from exploiting these symmetries. This project seeks to identify and exploit symmetries that are prevalent in cooperative AI tasks, where a group of multiple autonomous sequential decision makers, or agents, plan and learn to maximize their combined benefit. As an example, consider the application of adaptive traffic signal control, where each intersection can be modeled as an agent controlling its traffic signal in a way that adapts to real-time traffic conditions to reduce congestion. There exist certain symmetries when the topology of the road network is regular, e.g., as a 4-connected grid, and the road condition is uniform. When done properly, such multi-agent symmetries can be identified and exploited to greatly improve the efficiency and effectiveness of the current solutions to cooperative AI. This project also integrates the proposed research into an array of education initiatives, playing key roles in the curriculum development and undergraduate research experiences at the PI's university, as well as outreach activities that bridge academia with industry practitioners and community stakeholders.

This research will establish a unified framework and develop a set of interdependent methods that formulate, identify, and exploit mul

## Key facts

- **NSF award ID:** 2544948
- **Awardee organization:** Worcester Polytechnic Institute (MA)
- **SAM.gov UEI:** HJNQME41NBU4
- **PI:** Qi Zhang
- **Primary program:** 01002324DB NSF RESEARCH & RELATED ACTIVIT
- **All programs:** CAREER-Faculty Erly Career Dev, ROBUST INTELLIGENCE, EXP PROG TO STIM COMP RES
- **Estimated total:** $535,346
- **Funds obligated:** $387,654
- **Transaction type:** Continuing Grant
- **Period:** 07/01/2025 → 04/30/2028

## Primary source

NSF Award Search: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2544948

## Citation

> US National Science Foundation, Award 2544948, CAREER: Identifying and Exploiting Multi-Agent Symmetries. Retrieved via AI Analytics 2026-06-07 from https://api.ai-analytics.org/grant/nsf/2544948. Licensed CC0.

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