Abstract：In the scenario of air-to-air missiles intercepting large-scale swarms, because the performance of centralized algorithms to solve large-scale task assignment problems is limited by communication capabilities and real-time performance, it is practically important to develop distributed algorithms to solve task assignment problems. Based on the hedonic coalition game (HCG) model, this paper designs a distributed missile swarm task assignment model, and uses the spatial adaptive play (SAP) algorithm in the game learning algorithm to achieve the optimal allocation solution. The simulation comparison experiment with the centralized algorithm shows that the distributed task assignment model based on the HCG designed in this paper can solve the distributed task allocation problem with constraints, and has comparable optimization performance and better convergence efficiency.
张贇, 邱忠宇, 蔡云泽. 基于偏好联盟博弈的导弹集群分布式任务分配模型[J]. 空天防御, 2021, 4(3): 24-32.
ZHANG Yun, QIU Zhongyu, CAI Yunze . Distributed Task Assignment Model of Missile Swarm Based on Hedonic Coalition Games. Air & Space Defense, 2021, 4(3): 24-32.
