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The HoneyComb Paradigm for Research on Collective Human Behavior

The HoneyComb Paradigm for Research on Collective Human Behavior

Published on: January 19, 2019

Agent swarms: Cooperation and coordination under stringent communications constraint.

Paul Kinsler¹, Sean Holman², Andrew Elliott³

¹Department of Electronic & Electrical Engineering University of Bath, Bath, United Kingdom.

|December 11, 2024

Summary

This summary is machine-generated.

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This study introduces a novel model for agent swarms to connect in challenging communication environments. It focuses on agent-centric metrics and communication constraints for autonomous systems like drones and satellites.

Area of Science:

Robotics and Autonomous Systems
Network Communications
Distributed Systems

Background:

Swarms of autonomous agents (satellites, drones) are crucial for exploration.
Challenging communication environments pose significant hurdles for swarm connectivity.
Constraints like stealth, power, and hardware limitations necessitate new communication strategies.

Purpose of the Study:

To present a novel, discrete, geometry-free model for multi-agent swarm communications.
To develop agent-centric performance metrics for swarms without global location knowledge.
To analyze connectivity tactics under stringent communication constraints.

Main Methods:

Developed a discrete, geometry-free communication model for agent swarms.

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Proposed agent-centric performance metrics to address lack of global knowledge.

Simulated various connectivity tactics to evaluate outcomes, risks, and connectivity.

Main Results:

Demonstrated how communication constraints dominate algorithmic outcomes in swarm connectivity.
Showcased the impact of the information gain to information loss ratio on simulated outcomes.
Identified excessive round-trip-time checks as an effective filtering mechanism.

Conclusions:

The proposed framework enables testing of efficient communication tactics for agent swarms.
The model is applicable to diverse scenarios and future autonomous systems.
Agent-centric metrics and constraint-aware algorithms are vital for swarm communication success.