论文标题
惯性约束的两个代理调度的最小框架
A Minimax Framework for Two-Agent Scheduling with Inertial Constraints
论文作者
论文摘要
自主代理在智能运输和智能制造等应用中有希望，而安排代理必须考虑其惯性约束。当前的大多数研究都需要所有代理的服从，这在非专用系统（例如交通交叉点）中很难实现。在本文中，我们建立了一个最小值框架，用于安排两个惯性约束的代理，而没有合作假设。具体而言，我们首先为各种情况信息提供了统一和足够的表示，并定义一个状态值函数，以表征代理在给定情况下的国家偏好。然后，提出了Minimax控制策略以及计算方法，该方法在每个步骤中都优化了最差的状态值函数，并且还提供了策略的安全保证。此外，在拟议框架的适用场景上引入了一些概括。数值模拟表明，与排队和遵循策略相比，Minimax控制策略可以将最大的计划成本降低13.4 \％$。最后，也讨论了决策期，观察期和惯性约束的影响。
Autonomous agents are promising in applications such as intelligent transportation and smart manufacturing, and scheduling of agents has to take their inertial constraints into consideration. Most current researches require the obedience of all agents, which is hard to achieve in non-dedicated systems such as traffic intersections. In this article, we establish a minimax framework for the scheduling of two inertially constrained agents with no cooperation assumptions. Specifically, we first provide a unified and sufficient representation for various types of situation information, and define a state value function characterizing the agent's preference of states under a given situation. Then, the minimax control policy along with the calculation methods is proposed which optimizes the worst-case state value function at each step, and the safety guarantee of the policy is also presented. Furthermore, several generalizations are introduced on the applicable scenarios of the proposed framework. Numerical simulations show that the minimax control policy can reduce the largest scheduling cost by $13.4\%$ compared with queueing and following policies. Finally, the effects of decision period, observation period and inertial constraints are also numerically discussed.
