# Swarm Analytics: Designing Information Markers to Characterise Swarm Systems in Shepherding Contexts

arXiv: https://arxiv.org/abs/2208.12386 · HTML: https://mlsanity.com/paper/2208.12386/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 9 of its 110 references that are in the map.
- First posted on arXiv 26 Aug 2022.

## Builds on (most cited first, 9 of 9)

- [A Comprehensive Review of Shepherding as a Bio-inspired Swarm-Robotics Guidance Approach](https://mlsanity.com/paper/1912.07796/) (2019)
- [On Geometry of Information Flow for Causal Inference](https://mlsanity.com/paper/2002.02078/) (2020)
- [Onto4MAT: A Swarm Shepherding Ontology for Generalised Multi-Agent Teaming](https://mlsanity.com/paper/2203.12955/) (2022)
- [Anatomy of Leadership in Collective Behaviour](https://mlsanity.com/paper/1802.01194/) (2018)
- [mFLICA: An R package for Inferring Leadership of Coordination From Time Series](https://mlsanity.com/paper/2004.06092/) (2020)
- [Inferring network properties from time series using transfer entropy and mutual information: validation of multivariate versus bivariate approaches](https://mlsanity.com/paper/2007.07500/) (2020)
- [Learning Swarm Interaction Dynamics from Density Evolution](https://mlsanity.com/paper/2112.02675/) (2021)
- [Disturbances in Influence of a Shepherding Agent is More Impactful than Sensorial Noise During Swarm Guidance](https://mlsanity.com/paper/2008.12708/) (2020)
- [Vital Node Identification in Complex Networks Using a Machine Learning-Based Approach](https://mlsanity.com/paper/2202.06229/) (2022)

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

- [Contextually Aware Intelligent Control Agents for Heterogeneous Swarms](https://mlsanity.com/paper/2211.12560/) (2022)

## Abstract (arXiv)

Contemporary swarm indicators are often used in isolation, focused on extracting information at the individual or collective levels. Consequently, these are seldom integrated to infer a top-level operating picture of the swarm, its members, and its overall collective dynamics. The primary contribution of this paper is to organise a suite of indicators about swarms into an ontologically-arranged collection of information markers to characterise the swarm from the perspective of an external observertextemdash, a recognition agent. Our contribution shows the foundations for a new area of research that we tile swarm analytics, whose primary concern is with the design and organisation of collections of swarm markers to understand, detect, recognise, track, and learn a particular insight about a swarm system. We present our designed framework of information markers that offer a new avenue for swarm research, especially for heterogeneous and cognitive swarms that may require more advanced capabilities to detect agencies and categorise agent influences and responses.