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Updated: May 30, 2025

The HoneyComb Paradigm for Research on Collective Human Behavior

The HoneyComb Paradigm for Research on Collective Human Behavior

Published on: January 19, 2019

Human-inspired strategies for controlling swarm systems.

Patrick Nalepka^1,2, Gaurav Patil^1,2, Rachel W Kallen^1,2

¹Performance and Expertise Research Centre, Macquarie University, Sydney NSW 2109, Australia.

Philosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences

|January 29, 2025

Summary

This review examines human coordination strategies for controlling autonomous agents in swarm systems. Understanding these human behaviors informs the design of compatible artificial teammates for effective human-autonomy teaming.

Keywords:

human performance human–machine interaction multi-agent coordination

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Area of Science:

Robotics
Human-Computer Interaction
Collective Behavior

Background:

Human-autonomy teaming is crucial for controlling swarms.
Understanding human coordination is key to designing effective autonomous teammates.

Purpose of the Study:

To review human coordination behaviors in controlling evasive autonomous agents.
To inform the design of human-compatible teammates for swarm systems.
To explore artificial agents that mimic human dynamics for integration into teams.

Main Methods:

Summarized solutions from human dyads controlling agents.
Analyzed communication and labor division in four-person teams via simulations.
Reviewed designs of artificial agents using task-dynamical models.

Main Results:

Identified coordination strategies in human dyads.
Observed communication and division of labor in larger human teams.
Overviewed artificial agents replicating human-like dynamics.

Conclusions:

Human coordination behaviors are vital for swarm control.
Task-dynamical models can create human-like artificial agents.
Further research is needed on situation awareness and trust in human-autonomous swarms.