METHODOLOGICAL FOUNDATIONS FOR THE CREATION OF REGULARIZING ARTIFICIAL INTELLIGENCE METHODS TO ENSURE THE SUSTAINABILITY OF SOLUTIONS

UDC 004.8
DOI: 10.36871/2618-9976.2023.07.001

Authors

Svetlana V. Prokopchina,
Doctor of Technical Sciences, Professor, Financial University under the Government of the Russian Federation, Moscow, Russia

Abstract

The article shows the relevance of ensuring the sustainability of solutions of artificial intelligence systems. A methodological approach is proposed and the theoretical foundations for the creation of artificial intelligence methods with regularizing properties and providing stable solutions to problems in conditions of significant uncertainty are considered. The methodology is based on the regularizing Bayesian approach and scaling technologies based on it. Theorems and analytical dependencies for the creation of regularizing algorithms of artificial intelligence are given.

Keywords

Decision stability, Regularizing Bayesian approach, Artificial intelligence