The hunting of dynamic targets by multiUAV is an important problem in UAV swarm operations. In this paper, aiming at the dynamic target oriented swarm hunting problem, by analyzing the shortcomings of the hunting mechanism based on MADDPG algorithm, and learning from the attention mechanism used by Google machine translation team, we introduce the attention mechanism into the hunting process, design the cooperative hunting strategy based on the attention mechanism, and construct the corresponding hunting algorithm. Improve MADDPG based on AC framework. First of all, the attention module is added to critical network to process the information of all UAVs according to different attention weights; then, the attention module is added to actor network to promote other UAVs to carry out cooperative hunting. The simulation results show that AttMADDPG algorithm can improve the training stability by 8.9% and reduce the task completion time by 19.12% compared with MADDPG algorithm. After learning, the UAV can cooperate to make the swarm emerge more intelligent behavior.