Adaptive Force Ratio Allocation for Multi-UAV Cooperative Multi-Target Encirclement

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Abstract
The size of an unmanned aerial vehicle (UAV) swarm and the capabilities of each individual in the swarm are critical determinants of mission effectiveness in multi-target encirclement. This paper proposes a framework for strategic force allocation during mission execution. A lightweight estimator is designed to predict the required scale of UAV teams based on target difficulty indicators in the tested settings, including the number of hunted targets and their mobility. Owing to the computational efficiency of the Experience Library, the proposed framework can rapidly re-optimize UAV allocation when target difficulty changes or the available UAV budget is reduced, thereby enabling adaptive swarm resizing and resource redistribution under dynamic disturbances and constraints. Meanwhile, system performance under different force allocations is evaluated from two dimensions: mission success rate and time-to-target. The aim is to achieve mission lightweighting and avoid redundant resource consumption.

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