# Swarm Performance Indicators: Metrics for Robustness, Fault Tolerance, Scalability and Adaptability

arXiv: https://arxiv.org/abs/2311.01944 · HTML: https://mlsanity.com/paper/2311.01944/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 3 Nov 2023.

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

- [GNN-based Decentralized Perception in Multirobot Systems for Predicting Worker Actions](https://mlsanity.com/paper/2501.04193/) (2025)

## Abstract (arXiv)

Swarms have distributed control and so are assumed to inherently have superior robustness, scalability and adaptability compared to centralised multi-agent systems. However, these features have generally only been defined qualitatively and there is a lack of quantitative metrics and experimental measures for the claimed parameters. Swarm Performance Indicators are defined here as Key Performance Indicators for swarm features but can be applied to multi-agent systems with centralised control as well. These swarm features are Robustness, Fault Tolerance, Adaptability and Scalability. Swarm Performance Indicators can be used to highlight the benefits of swarms beyond solely considering task-based performance metrics (e.g. time taken)