Abstract: Due to the limitation of individual capability and penetration means, a single red aircraft is difficult to penetrate successfully from multiple blue interceptors. To solve this problem, an intelligent game strategy based on reinforcement learning is designed. Firstly, the mathematical model of the red aircraft is established, including throwing bait, maneuvering adjustment, attitude adjustment, etc. Secondly, the mathematical model of the blue aircraft is established, and the blue intercepts the red with the proportional guidance method. Next, a flight escape algorithm based on deep deterministic policy gradient is designed. Then, by combining the prior knowledge pre-training and the preferred experience playback mechanism, the learning speed and the convergence speed of the algorithm are accelerated. The simulation results show that the proposed algorithm can make the red aircraft penetrate successfully when facing the blue interceptors.