Research on the individualization of human-computer interaction through socially sensitive learning

With the continuous development of robotics, the interaction between robots and humans has become more and more important. It must be pointed out that whether it is a human (user) or a robot, personality is the basic element of human-computer interaction. A large number of studies have shown that adapting the personality and behavior of robots to human characteristics can make interactions more attractive. Therefore the topic of current research is that robots can automatically learn user preferences. In other words, reinforcement learning is combined with human and social signals as the basis of algorithms. This article designs an example scenario, using a robot as a teacher to teach, it can express his personality in the form of language style by generating natural language and adapting it to each student and considering social signals.