USING THE MULTI-AGENT MODELING FOR LONG-TERM FORECASTING OF THE BEHAVIOR OF ECONOMIC AGENTS

Abstract

Background. The need for long-term forecasting of the behavior of economic agents is largely determined the development of modern economics. The actualization of the need for behavior modeling led to the creation of a new branch of knowledge – behavioral economics. The significance of the study of economic behavior has become increasingly relevant in recent times against the background of the transition to a digital economy. The purpose of the study is to determine how effective the use of multi-agent modeling is for long-term forecasting of the behavior of economic agents. Materials and methods. The methodology for studying the behavior of economic agents is characterized by interdisciplinarity. The need for an interdisciplinary approach can be explained by the youth of behavioral economics and, accordingly, the insufficient elaboration of its own methodology. Thus, one of the main methods for studying the behavior of economic agents is simulation modeling. Simulation has arisen as a subdivision of mathematical modeling and was initially used mainly in the natural sciences, but now it finds its application in a variety of scientific fields. The implementation of research tasks was carried out based on the analysis of existing simulation models. Over the past few decades, simulation modeling has evolved from the simplest physical models to the most complex hybrid, multiagent models. Such models as multi-agent have a special significance for our research. Undoubtedly, an increase in the accuracy of modeling will continue with the development of science and computer technology. Results. The analysis of simulation models used in predicting the behavior of economic agents, allows to identify the most effective method of modeling. Based on the chosen modeling method, a long-term forecasting algorithm is developed for the behavior of economic agents. The analysis of the multi-agent model, which simulates the decision-making process of agents to change jobs. Conclusions. The study of forecasting indicators using comparative analysis allows us to conclude that among the existing methods for modeling the behavior of economic agents, multi-agent modeling is the most adequate.

Keywords

• multi-agent modeling
• long-term forecasting
• economic agents