Abstract

This paper aims to introduce three types of understanding models from the perspective of human cognitive systems and machine information processing. The method steps are as follows: 1. Obtain a complete all equal formal understanding model (A) by constructing a twin Turing machine between numbers and numbers. 2. Obtain an approximately equal intelligent understanding model (B) by constructing a twin Turing machine between numbers and symbols. 3. Obtain a similar socialized understanding model (C) by constructing a twin Turing machine between numbers and characters, which is characterized by: the model A to B and then C gradually converge. As a result, it was found that the machine formal information processing and the human content information processing are opposite in convergence. It is clear that the combination of the three formalized understanding models and the bilingual model of interpretative translation is the key to formal understanding, intelligent understanding and social understanding. Based on them, ambiguity, misunderstanding and understanding are all well understood. The significance is that it proves that the three types of understanding models and the two sets of convergence modes can effectively determine the formal understanding process. Furthermore, it is clear that the ways of human and computer are combined completely which is better than pure humans or simple machines. That can be applied to cognitive systems and information processing perfectly. And its application is in the combination of human-machine-specific personalized ability training and standardized knowledge learning and management, especially based on the targeted reuse of subject knowledge centers.