Multi-Agent Task Negotiation Among UAVs to Defend Against Swarm Attacks
Abstract
This research involves a multi-agent based simulation modeling a large swarm of adversarial unmanned aerial vehicles (UAVs) attacking a surface target and groups of friendly UAVs responding to thwart the attack. Defense systems need to cooperatively negotiate which enemy systems to engage to maximize the number of aggressor systems destroyed. The research questions we wish to explore are as follows: (1) Do decentralized assignment methods approach centralized methods' effectiveness in complex scenarios with a large number (up to 150 aggressor vs. 450 defender) of agents?; (2) How much do other factors in a complex scenario contribute to a blue team's defence capability as compared to the assignment method (i.e., is assignment method a major factor in blue's effectiveness)?; and (3) What are the tradeoffs between global and local information availability versus performance? Using optimal centralized task assignment methods as a baseline, various distributed methods are examined for efficiency and effectiveness. Our findings indicate that the optimality of distributed methods approaches that of centralized methods, though further study is warranted in future simulations with additional constraints, and in field experimentation with physical UAVs. We further find that the number of defender agents, the effectiveness of their weapon systems, and their speed contribute significantly to the defender swarm's effectiveness.
Document Details
- Document Type
- Technical Report
- Publication Date
- Mar 01, 2012
- Accession Number
- ADA560588
Entities
People
- Michael Day
Organizations
- Naval Postgraduate School