论文标题
网络物理系统中自主子系统的协调和沟通：一种机制学习方法
Coordination and Communication of Autonomous Subsystems in Cyber Physical Systems: A Mechanism Learning Approach
论文作者
论文摘要
在控制许多自主子系统（例如自动驾驶汽车或无人机网络）的控制中，集中式控制可能会受到过度复杂性，有限的通信带宽或子系统私人信息的阻碍。因此，控制中心可以通过设计定价等机制来协调子系统的控制，这使得子系统动力学的局部优化也可以最大程度地提高整体系统的奖励，即社会福利。机制设计的经济学框架用于自主子系统的协调。为了解决传统经济学机制设计中未考虑的动态挑战以及私人信息的复杂性，通过将不同的几何结构赋予问题，采用了几何和机器学习的方法。理论框架应用于城市空中流动性的背景下，其中数值模拟显示了拟议框架的有效性。
In the control of many autonomous subsystems, such as autonomous vehicles or UAV networks, a centralized control may be hindered by the prohibitive complexity, limited communication bandwidth, or private information of subsystems. Therefore, it is desirable for the control center to coordinate the controls of subsystems by designing mechanisms such as pricing, which makes the local optimizations of subsystem dynamics also maximize the reward of the total system, namely the social welfare. The economics framework of mechanism design is employed for the coordination of the autonomous subsystems. To address the challenge of dynamics, which are not considered in conventional economics mechanism design, and the complexity of private information, the approaches of geometrization and machine learning are employed, by endowing different geometric structures to the problem. The theoretical framework is applied in the context of urban aerial mobility, where the numerical simulations show the validity of the proposed framework.
