Abstract: To improve the capability of carrier aircrafts sortie and recovery, a theory of apprenticeship learning, came of the robot navigation and control domain, was applied to automate the process of sortie and recovery scheduling. Firstly, a simulation model of aircrafts sortie and recovery was established based on the frame of Markov decision process. Then, taking an expert's demonstration operation as learning former, an optimized scheduling policy was created with the multiplicative weights apprenticeship learning algorithm. Compared with the optimization results of the two typical research cases in the condition of group sortie and continuous sortie with the expert's demonstration, the algorithm shows a better performance and function.