# CAREER: Timely, Efficient, and Risk-Aware Control and Communication Policies for Networked Multi-Agent Systems

> **NSF 01002526DB NSF RESEARCH & RELATED ACTIVIT** · University of North Carolina at Charlotte (NC) · $504,913

## Abstract

Networked Multi-agent Systems (NMS), such as fleets of drones, connected autonomous vehicles, or smart power-grids, consist of multiple plants, controllers, and sensors exchanging data over a shared communication network managed by a network manager. This network manager allocates communication services (CS), such as bandwidth, reliability, and latency, to each agent, enabling sensors to transmit data to their respective controllers. For optimal NMS performance, the problem must be jointly studied at the agent level and the network level. Agents need to design communication-aware controllers, while the network manager must allocate communication services in a control-aware manner. Specifically, agents must develop controllers that proactively incorporate allocated communication services, analyzing their impact on sensor data quality, timing, and resolution. Simultaneously, the network manager must dynamically allocate communication resources to meet agents' evolving needs while ensuring fairness in allocations across all agents. At its core, this problem requires developing an optimal control-communication theory to guide decision-making for both agents and the network manager. The proposal envisions enabling optimal decision-making for NMS across various domains: from enhancing coordination and cooperation in multi-robot systems to optimizing information exchange among connected and autonomous vehicles to voltage and frequency control in power-grids.  With advancements in c

## Key facts

- **NSF award ID:** 2443349
- **Awardee organization:** University of North Carolina at Charlotte (NC)
- **SAM.gov UEI:** JB33DT84JNA5
- **PI:** Dipankar Maity
- **Primary program:** 01002526DB NSF RESEARCH & RELATED ACTIVIT
- **All programs:** Control systems & applications, CAREER-Faculty Erly Career Dev, Cyber-Physical Systems, CONTROL SYSTEMS, LEARNING & INTELLIGENT SYSTEMS
- **Estimated total:** $504,913
- **Funds obligated:** $504,913
- **Transaction type:** Standard Grant
- **Period:** 06/15/2025 → 05/31/2030

## Primary source

NSF Award Search: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2443349

## Citation

> US National Science Foundation, Award 2443349, CAREER: Timely, Efficient, and Risk-Aware Control and Communication Policies for Networked Multi-Agent Systems. Retrieved via AI Analytics 2026-06-07 from https://api.ai-analytics.org/grant/nsf/2443349. Licensed CC0.

---

*[NSF Awards dataset](/datasets/nsf-awards) · CC0 1.0*