【摘要】 集群系统在拒止环境中显现出突出的应用潜力,敌我双方集群系统之间的对抗将是未来主要作战形态之一.针对资源有限或决策受限的集群对抗场景中,双方智能体决策变量相互耦合以及存在约束的情况,基于多联盟非合作博弈理论建立集群对抗模型,通过设计多联盟非合作博弈理论的纳什均衡搜索算法得到分布式集群的最优策略.定义了一种基于时变编队跟踪的干扰与反干扰场景,验证了该算法仿真结果的有效性.更多还原

【Abstract】 Swarm systems have shown outstanding application potential in refusal environments, and the con-frontation between enemy and friendly cluster systems will be one main form of combat in the future. According to the swarm confrontation scenarios with limited resources or decision-making, the mutual coupling and constrained decision-making variables of agents of both sides exist. The swarm confrontation model is established based on multi coalition noncooperative games. By designing a Nash equilibrium searching algorithm for multi coalition noncooperative games, the optimal strategy of distributed swarm is obtained. Finally, the interference and anti-interference scenarios based on time-varying formation tracking is defined to verify the effectiveness of the simulation results of the proposed algorithm.更多还原