# Lightweight Decentralized Neural Network-Based Strategies for Multi-Robot Patrolling

arXiv: https://arxiv.org/abs/2412.11916 · HTML: https://mlsanity.com/paper/2412.11916/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 16 Dec 2024.

## Built on by (most cited first, 1 of 1)

- [Time-Constrained Intelligent Adversaries for Automation Vulnerability Testing: A Multi-Robot Patrol Case Study](https://mlsanity.com/paper/2509.11971/) (2025)

## Abstract (arXiv)

The problem of decentralized multi-robot patrol has previously been approached primarily with hand-designed strategies for minimization of 'idlenes' over the vertices of a graph-structured environment. Here we present two lightweight neural network-based strategies to tackle this problem, and show that they significantly outperform existing strategies in both idleness minimization and against an intelligent intruder model, as well as presenting an examination of robustness to communication failure. Our results also indicate important considerations for future strategy design.