关键词: 群集智能, 协同攻击, 多目标分配, 空战, 决策, 超视距

Abstract: In modern air combat, it is an important yet difficult task to coordinate multi-fighter to make multi-target attack decisions by using the tactical digital information links (TADILs ) to share and exchange combat information. To address the problem, a novel distributed heterogeneous multi-target air combat decision-making model is proposed based on the collective intelligence (COIN) theory put forward by the NASA/Ames Research Center. In this model, each missile is defined as an agent and the conventional COIN framework is expanded by agent contribution rate to realize accurate convergence under a distributed heterogeneous agent environment. In order to improve the convergence rate, two classes of heuristic information is added to the algorithm, i.e., constructive heuristics and improvement heuristics, to reduce blind search in intermediate results and enhance convergence rate in ultimate results. Simulation results show that as compared with conventional methods, the proposed method is able to converge to the global optimum with more stability and higher expandability, decrease the amount of computation and improve convergence rate.

Key words: collective intelligence, coordinated attack, multi-target assignment, air combat, decision making, beyond visual range