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Arxiv
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ARBoids: Adaptive Residual Reinforcement Learning With Boids Model for Cooperative Multi-USV Target Defense
- Researchers introduced ARBoids, an adaptive residual reinforcement learning framework for the target defense problem with unmanned surface vehicles (USVs).
- ARBoids integrates deep reinforcement learning (DRL) with the Boids model for multi-agent coordination in challenging interception scenarios.
- In simulations, ARBoids demonstrated superior performance compared to traditional interception strategies and showed adaptability to attackers with varying maneuverability.
- The code for ARBoids will be made available upon the acceptance of this research letter.
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