The multi-task area reconnaissance decision-making problem in an uncertain environment is considered, and the entire task-performing process is divided into two stages.According to the information of reconnaissance task areas and the performance of the UAV itself, a discrete Cuckoo Search Algorithm (CSA) is adopted to solve the reconnaissance route optimizing problem, so that the reconnaissance path of the entire task area is the shortest.Then, according to the characteristics of the task load and the reconnaissance task area, and under the premise of ensuring the reconnaissance of the entire task area and the minimum reconnaissance gains, the improved CSA is used to allocate the optimal task reconnaissance time for each reconnaissance task area, so that the information gains in the entire reconnaissance process is the maximum.Simulation results have proved the effectiveness and feasibility of the proposed algorithm.Compared with classic genetic algorithms, the improved CSA has a higher operating efficiency on such reconnaissance decision-making problems.It provides a reference for the scientific decision-making of UAV multi-task area reconnaissance optimizing problem.