Multi-agent RL policies for heterogeneous sUAS fleets reach equilibria for safe separation in package delivery simulations, outperforming some rule-based baselines but favoring stronger configurations.
Asynchronous methods for deep reinforcement learning
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Separation Assurance between Heterogeneous Fleets of Small Unmanned Aerial Systems via Multi-Agent Reinforcement Learning
Multi-agent RL policies for heterogeneous sUAS fleets reach equilibria for safe separation in package delivery simulations, outperforming some rule-based baselines but favoring stronger configurations.