Agent-based modeling as a tool for analyzing complex economic processes
Rubrics: SCIENTIFIC ARTICLES
Authors:
1.
Kuban State Agrarian University
student
student
2.
Kuban State Agrarian University
student
student
3.
Kuban State Agrarian University
(kafedra ekonomicheskoy kibernetiki, assistent)
employee
employee
Type:
Article
Pages:
from 295
to 298
Status:
Published
Received:
04.06.2025
Accepted:
09.06.2025
Published:
09.06.2025
Subject area:
330.45
Language:
Russian
Keywords:
agent-based modeling, economics, supercomputer technologies, forecasting
Abstract (English):
This article discusses agent-based modeling (ABM) as a modern method for studying complex economic systems. ABM makes it possible to analyze the interaction of various autonomous agents, simulate their behavior, and make forecasts for the further development of economic processes. This method is especially effective in simulating various nonlinear processes, crisis phenomena, and emergent properties in agent interactions. Particular attention is paid to the use of supercomputer technologies, which significantly increase the capabilities of ABM, which in turn allows increasing the scale of models, their accuracy, and detail. Examples of successful use of ABM in both global and Russian practice are given, including the creation of financial market models, the dissemination of innovations, and the optimization of logical systems. Possible prospects for the development of this method for economic research were also discussed.
This article discusses agent-based modeling (ABM) as a modern method for studying complex economic systems. ABM makes it possible to analyze the interaction of various autonomous agents, simulate their behavior, and make forecasts for the further development of economic processes. This method is especially effective in simulating various nonlinear processes, crisis phenomena, and emergent properties in agent interactions. Particular attention is paid to the use of supercomputer technologies, which significantly increase the capabilities of ABM, which in turn allows increasing the scale of models, their accuracy, and detail. Examples of successful use of ABM in both global and Russian practice are given, including the creation of financial market models, the dissemination of innovations, and the optimization of logical systems. Possible prospects for the development of this method for economic research were also discussed.
Keywords:
agent-based modeling, economics, supercomputer technologies, forecasting
agent-based modeling, economics, supercomputer technologies, forecasting
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