Abstract: Re-orientation involves rotating an object to a target configuration, with the most challenging case being the rotation from an arbitrary initial configuration to an arbitrary target configuration. To address the challenge of efficiently performing in-hand re-orientation tasks in a more human-like manner by guiding anthropomorphic five-fingered dexterous hands with different degrees of actuation (DoA), a target position-guided in-hand object re-orientation policy generation method is proposed. Firstly, a feasible principle for designing target positions is proposed, inspired by the operation characteristics of human hands during in-hand re-orientation and based on the distribution characteristics of DoA in anthropomorphic five-fingered dexterous hands. The difference between the actual and target positions of the object during re-orientation process is utilized as a component of the immediate reward to guide anthropomorphic five-fingered dexterous hands in maintaining the object near the target. Secondly, a method is developed inspired by the preparatory states of human hands before performing re-orientation tasks, to sample the joint positions of anthropomorphic five-fingered dexterous hands when resetting the state everytime, aiming to enhance manipulation capabilities. Finally, the re-orientation policy is trained using the proximal policy optimization (PPO) algorithm based on the long short-term memory (LSTM) network and asymmetric actor-critic architecture. Simulation results show that the proposed method enables the 9-DoA Schunk SVH dexterous hand, the 13-DoA BICE dexterous hand developed by Beijing Institute of Control Engineering (BICE), and the 18-DoA Shadow dexterous hand to approach the predefined maximum number of consecutive successes when performing re-orientation tasks. Moreover, compared with in-hand object re-orientation policy generation method without target position guidance, the proposed method significantly reduces the average number of steps required to perform re-orientation tasks. The proposed method enables anthropomorphic five-fingered dexterous hands with different DoA to efficiently perform object re-orientation tasks in a human-like manner through coordinated action of the palm and fingers, significantly enhancing operational efficiency.