A Computational System of Psycholinguistic Fuzzy Inference Under Uncertainty

The modern intelligent systems of the Narrow Artificial Intelligence (NAI) cannot independently and continuously think, reason, cognize, and carry out a Logical Inference, based on these computational reasonable functions under: a) uncertainty, b) time changing of the situations and objects of surrounding environment, and c) without using of the human's intellect for retrain (reprogramming) these systems. For a solution of these NAI's problem and in order to create a new reasonable generation of Artificial Intelligence Fuzzy Logic Inference Subsystem (AIFLIS), in this paper is proposed the conception, model, method and subsystem for modeling of the Computational Psycholinguistic and Cognitive Fuzzy Inference in the identified Subject Domain by implementation of the following Computational Brain's computational subsystems: a) identification and preprocessing of the psycholinguistic, lingual, sound, signal. and other meanings of objects, associated with the images of the subject area, and b) situational fuzzy control of computational memory, decision-making, reasoning, thinking, consciousness, awareness, cognition, intuition, wisdom, and others. To implement of the AIFLIS functionality, have been applied the Situational Control, Fuzzy Logic, Psycholinguistics, Data Science, and Informatics.