Abstract: We use multi-agent systems to solve conflicts between drone flight paths (4D contracts) in urban traffic, installing safety and service quality. Intuitive corrective actions are chosen considering delay, quality, and energy. We explore different algorithms based on graph search, auctions, and distributed optimization for decision-making and action evaluation. We test these in a simulated surveillance scenario with unforeseen emergency trajectories.
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