Cognitive Perception as a Base Model of the Feeling Artificial Intelligence

Abstract

The need for more advanced Unmanned Systems (US) is supported by the development trends of world society. Artificial Intelligence (AI) plays an important role in maintaining the required level of US autonomy. AI-enabled US developers are focusing on the creation of the third generation of AI namely Feeling AI (FAI) for Autonomous Intelligent US (AIUS). One of the components of the FAI is a Cognitive Perception (CP) model, which overcomes the gap between the two paradigms "data from sensors" and "natural words", which was and is the main problem for the deployment of AIUS. The CP model considered in the work takes into account such cognitive processes as the mapping of data from sensors in iconic memory and its further processing in short-term memory by generalizing and abstracting in order to distill the sense of sensor data and represent it in the form of concepts. An important feature of cognitive perception is the sustainable aging of information and its forgetting over time. The article considers an algorithm that implements a model of cognitive perception with an aging mechanism. The results of computer experiments in which a wheeled warehouse robot was used as an AIUS showed that by adjusting the aging rate coefficients included in the CP model in accordance with the dynamic characteristics of the environment, it is possible to minimize the risks of violating the autonomy of the AIUS when making decisions in conditions of incomplete information.