Multi-Agent Task Negotiation Among UAVs to Defend Against Swarm Attacks
Chung, Timothy H.
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This research involves a multi-agent based simulation modeling a large swarm of adversarial 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. 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 does approach 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 speeds contribute significantly to the defender swarm’s effectiveness.
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