基于多智能体联盟的多机协同空战任务分配

基于多智能体联盟形成理论，分析了网络化条件下多平台多目标攻击任务分配问题。将协同任务分配的过程视为复杂联盟的生成过程，首先将对目标总体的打击任务分解为一系列子任务，各子任务再进一步分解为单个平台能够完成的任务单元；再根据联盟特征函数的定义分别建立联盟报酬、能力成本、通信开销模型，以联盟特征函数作为空战任务分配目标函数；最后引入离散粒子群优化算法进行联盟生成，采用二进制矩阵编码形式，设计粒子可行性检查策略。仿真实验验证了本方法在协同制导条件下空战任务分配的合理性与有效性。

Task allocation in cooperative air combat based on multi-agent coalition

Multi-agent coalition formation theory was used to analyze the task allocation of multi-aircraft against multi-target in net warfare combat. The process of cooperative air combat task allocating was just the process of coalition formatting. First, the whole striking task to all the targets was separated into a serious of subtasks, then the subtasks were decomposed to some task cells that can be executed by single platform. Second, the models of coalition reward, the ability cost and the communication spending were constructed based on the definition of the coalition characteristic function which was set as the object function of the air combat task allocation. Finally, particle swarm optimization was adopted in the form of binary matrix particle coding to generate the coalition, and the feasibility checking strategy of the particle was designed. Simulation studies were carried out to confirm the rationality and validity of the method in the cooperative air combat task allocation.