# A Cooperative Multi-Agent Probabilistic Framework for Search and Track Missions

arXiv: https://arxiv.org/abs/2302.10723 · HTML: https://mlsanity.com/paper/2302.10723/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 21 Feb 2023.

## Built on by (most cited first, 3 of 3)

- [Decentralized Multi-Agent Active Search and Tracking when Targets Outnumber Agents](https://mlsanity.com/paper/2401.03154/) (2024)
- [Adaptive Out-of-Control Point Pattern Detection in Sequential Random Finite Set Observations](https://mlsanity.com/paper/2506.23802/) (2025)
- [Fast Neural-Network Approximation of Active Target Search Under Uncertainty](https://mlsanity.com/paper/2604.22254/) (2026)

## Abstract (arXiv)

In this work a robust and scalable cooperative multi-agent searching and tracking framework is proposed. Specifically, we study the problem of cooperative searching and tracking of multiple moving targets by a group of autonomous mobile agents with limited sensing capabilities. We assume that the actual number of targets present is not known a priori and that target births/deaths can occur anywhere inside the surveillance region thus efficient search strategies are required to detect and track as many targets as possible. To address the aforementioned challenges we recursively compute and propagate in time the searching-and-tracking (SAT) density. Using the SAT-density, we then develop decentralized cooperative look-ahead strategies for efficient searching and tracking of an unknown number of targets inside a bounded surveillance area.