Cognitive process and information processing model based on deep learning algorithms.

Abstract

According to the developmental process of infants, cognitive abilities are divided into four stages: the Exploration Stage (ES), the Mapping Stage (MS), the Phenomena-causality Stage (PCS), and the Essence-causality Stage (ECS). The MS is a training of the consecutive characteristics of events, similar to a deep learning model; the PCS is a process that symbolizes the input and output of the mapping training, and uses these symbols as the input or output of the mapping training again. After training, the next possible symbol can be predicted, which is equivalent to recognizing the essence. Expressing the essence itself with a function in the ECS represents entering the scope of science. To illustrate the above process, take the evolution journey of an insectoid with only visual and compositional detection capabilities as an example. Without the need for additional learning algorithm programming, the insectoid evolves according to the Cognitive Process and Information Processing Model and can develop its own independent symbol system. The ability to develop its own unique symbolic system actually indicates the birth of an agent.