Agent modeling in research and forecasting of socio-economic systems and processes

 
PIIS042473880010550-4-1
DOI10.31857/S042473880010550-4
Publication type Article
Status Published
Authors
Affiliation: Ufa federal research center of the Russian academy of sciences
Address: Russian Federation,
Journal nameEkonomika i matematicheskie metody
EditionVolume 57 Issue 1
Pages19-32
Abstract

The all-pervasive digitalization, which is a process of digitizing not only the quantitative, but also the qualitative aspects of real-world objects, creates new challenges and new opportunities for humanity. The embodiment of such opportunities, in particular, is the use of a growing amount of data in science. And we are talking here not only about classical statistical methods, but also about complex neural network and simulation approaches, many of which are already successfully applied in science today. This work is devoted to the study of the experience of applying one of these approaches, agent-based modeling. This methodology is universal and allows you to reproduce socio-economic systems and processes of various degrees of complexity. Limitations in its application can only be the theoretical knowledge of the researcher and / or the computing power of the platform for implementing simulation models.

The first part of the article describes the genesis of agent modeling, discusses its philosophical and methodological foundations. In particular, it has been shown that certain elements of the agent-based approach intersect with the philosophical concepts of atomism, mechanism, and statistical mechanics. The second part is devoted to the analysis of the experience of applying agent modeling to the study of socio-economic systems and processes. In conclusion, the development trends of agent modeling and promising areas of its application are discussed.

Keywordsagent-based approach, simulation, socio-economic systems and processes, computer technology, information technology, cognitive technology, cybernetics
AcknowledgmentThe reported study was funded by RFBR, project number 19-110-50165
Received16.07.2020
Publication date29.03.2021
Number of characters78075
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