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.
Karagodin et al. (Mon,) studied this question.
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