The ever-changing environment and complex combat missions create new demands for the formation of mission groups of unmanned combat agents.This study aims to address the problem of dynamic construction of mission grou...The ever-changing environment and complex combat missions create new demands for the formation of mission groups of unmanned combat agents.This study aims to address the problem of dynamic construction of mission groups under new requirements.Agents are heterogeneous,and a group formation method must dynamically form new groups in circumstances where missions are constantly being explored.In our method,a group formation strategy that combines heuristic rules and response threshold models is proposed to dynamically adjust the members of the mission group and adapt to the needs of new missions.The degree of matching between the mission requirements and the group’s capabilities,and the communication cost of group formation are used as indicators to evaluate the quality of the group.The response threshold method and the ant colony algorithm are selected as the comparison algorithms in the simulations.The results show that the grouping scheme obtained by the proposed method is superior to those of the comparison methods.展开更多
基金Project supported by the National Natural Science Foundation of China(No.61773066)the Foundation of China Academy of Railway Sciences Corporation Limited(No.2019YJ071)。
文摘The ever-changing environment and complex combat missions create new demands for the formation of mission groups of unmanned combat agents.This study aims to address the problem of dynamic construction of mission groups under new requirements.Agents are heterogeneous,and a group formation method must dynamically form new groups in circumstances where missions are constantly being explored.In our method,a group formation strategy that combines heuristic rules and response threshold models is proposed to dynamically adjust the members of the mission group and adapt to the needs of new missions.The degree of matching between the mission requirements and the group’s capabilities,and the communication cost of group formation are used as indicators to evaluate the quality of the group.The response threshold method and the ant colony algorithm are selected as the comparison algorithms in the simulations.The results show that the grouping scheme obtained by the proposed method is superior to those of the comparison methods.
