Research on Multi Missile Maneuvering Strategy Based on MADDPG Algorithm
In recent years,with the further deepening of artificial intelligence research and the shine of related technologies on the battle-field of Russia and Ukraine,it has become more and more important in the military field.In view of increasingly complex battlefield environ-ment,current missile penetration field has problems such as high information dimension,slow command response,and inflexible penetration maneuver tactics.A training method based on multi-agent deep deterministic strategy gradient(MADDPG)is proposed to quickly generate missile attack maneuver schemes to assist commanders in making battlefield decisions.At the same time,the experience playback strategy of the algorithm is improved,and the experience pool filtering mechanism is added to shorten the training time and meet the rapid response re-quirements in real scenarios.By setting the multi-target rapid interception strategy,the simulation verifies that the maneuvering strategy ad-vantages of the designed method can penetrate defense,intelligently and collaboratively strike the target.Compared with other algorithms,the method can improve the convergence speed of 8％and success rate of 10％.
multi-agentMADDPGreinforcement learningcoordinated mobile penetrationmissile maneuvering
万方数据
维普
