arXiv cs.MA· Christian Manasseh, Savana Ammons·· 11 小时前AI 评分18
多无人机机队协同检测方法选择的博弈论决策框架
A Game-Theoretic Decision Framework for Optimal Selection of Coordination Detection Methods in Multi-UAV Fleet Operations
AI 导读
该研究提出一个博弈论决策框架，将多无人机机队协同检测中的方法选择建模为 Monitor 与 Nature 之间的两人零和博弈，通过 minimax 求解给出保证最坏情况性能的混合策略。
正文 · 原文
Abstract:Detecting coordination among unmanned aerial vehicle (UAV) fleets operating in shared airspace and identifying the route-lead aircraft whose navigation decisions govern fleet behavior presents a fundamental speed--accuracy trade-off: fast methods enable real-time traffic management but sacrifice detection fidelity, while accurate methods may exceed the time budget for actionable airspace deconfliction. This paper presents a game-theoretic decision framework that resolves this trade-off by formulating method selection as a two-player zero-sum game between a Monitor (selecting computational methods and parameters) and Nature (selecting the unknown traffic scenario). We construct an end-to-end pipeline from trajectory surveillance data through eight candidate detection algorithms, a Monte Carlo sensitivity analysis characterizing their stochastic performance, and finally a multi-objective optimization layer that identifies Pareto-optimal method portfolios. The minimax solution provides a robust mixed strategy with a probability distribution over methods that guarantees worst-case performance regardless of scenario uncertainty. Experimental evaluation across 200 randomized configurations spanning 5--50 aircraft demonstrates that the framework recommends distinct method portfolios depending on operational priority: Koopman Phase dominates balanced (70.6%) and speed-priority (79.7%) profiles, while CRQA emerges as primary (47.4%) when route-lead identification is prioritized. The framework achieves a guaranteed game value of 0.29--0.53 (normalized utility) across all tested preference profiles, providing the first principled, scenario-adaptive methodology for computational method selection in UTM fleet monitoring operations.
| Subjects: | Multiagent Systems (cs.MA); Computer Science and Game Theory (cs.GT); Systems and Control (eess.SY) |
| ACM classes: | I.2.11; I.2.8; G.1.6; G.3; I.6.3 |
| Cite as: | arXiv:2606.02383 [cs.MA] |
| (or arXiv:2606.02383v3 [cs.MA] for this version) | |
| https://doi.org/10.48550/arXiv.2606.02383 arXiv-issued DOI via DataCite |
Submission history
From: Savana Ammons [view email]
[v1]
Mon, 1 Jun 2026 15:33:12 UTC (385 KB)
[v2]
Fri, 5 Jun 2026 19:17:17 UTC (386 KB)
[v3]
Tue, 3 Nov 2026 23:03:32 UTC (1,716 KB)
来源：arXiv cs.MA · arxiv.org