发表机构
MIT; Caltech; ETH Zurich（麻省理工学院; 加州理工学院; 苏黎世联邦理工学院）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
针对去中心化先进空中交通中多智能体轨迹规划对均衡轨迹假设不现实的问题，提出策略鲁棒博弈公式，在有限扰动预算下保持精确动态势博弈性质并获准闭式解，实验表明能提升高风险场景鲁棒性且开销小。
AI 中文摘要
全球航空当局期望先进空中交通（AAM）管理在服务提供商之间实现去中心化，要求AAM航班通过预测其他航班的控制输入来自主规划轨迹，而非依赖集中式协调。将多智能体碰撞避免建模为精确动态势博弈的博弈论方法能够高效找到开环均衡，但这些方法假设智能体严格遵循其均衡轨迹——鉴于执行、感知和计算中的不确定性，这一假设并不现实。我们提出一种策略鲁棒的公式化方法，其中每个智能体防御一个虚构的对手，该对手在每个时间步在有限预算内扰动其他智能体的控制输入，以最小化该时间步的距离。我们证明，在智能体距离成本和鲁棒性水平的合理假设下，策略鲁棒博弈仍为精确动态势博弈，并在线性动力学下为内部对抗问题提供准闭式解，从而限制计算开销。使用对数距离成本、最多八个智能体的实验表明，策略鲁棒性在高碰撞风险配置中选择更鲁棒的轨迹，同时几乎不改变低风险轨迹，仅带来适度的运行时间增加。
英文摘要
Aviation authorities worldwide expect Advanced Air Mobility (AAM) traffic management to be decentralized among service providers, requiring AAM flights to autonomously plan trajectories by predicting other flights' control inputs rather than relying on centralized coordination. Game-theoretic approaches that formulate multi-agent collision avoidance as an exact dynamic potential game can efficiently find open-loop equilibria, but they assume that agents exactly follow their equilibrium trajectories---an unrealistic assumption given uncertainties in actuation, perception, and computation. We propose a strategically robust formulation where each agent protects against a fictitious adversary that, for each timestep, perturbs other agents' control inputs within a bounded budget to minimize distance at that timestep. We show that, under reasonable assumptions on agents' distance cost and robustness levels, the strategically robust game remains an exact dynamic potential game and admits a quasi-closed-form solution to the inner adversarial problem for linear dynamics, which limits computational overhead. Experiments with up to eight agents using logarithmic distance costs show that strategic robustness selects more robust trajectories in high-collision-risk configurations while leaving low-risk trajectories nearly unchanged, with only a modest increase in runtime.
Comments7 pages, 5 figures, accepted to CDC 2026
