moitvivt Моделирование, оптимизация и информационные технологии Modeling, Optimization and Information Technology 2310-6018 Издательство 368 КРУПНОМАСШТАБНЫЕ АГЕНТ-ОРИЕНТИРОВАННЫЕ МОДЕЛИ И ИХ ТЕХНИЧЕСКАЯ РЕАЛИЗАЦИЯ НА СУПЕРКОМПЬЮТЕРАХ LARGE-SCALE AGENT-BASED MODELS AND THEIR TECHNICAL IMPLEMENTATION ON SUPERCOMPUTERS Агеева Алина Фагимовна Ageeva Alina Fagimovna ageevaalina@yandex.ru aff-1 Центральный экономико-математический институт РАН Central Economics and Mathematics Institute of RAS 01 01 2026 1 1 e368 Copyright © Авторы, 2026 2026 This work is licensed under a Creative Commons Attribution 4.0 International License

В статье приведен обзор разработанных за рубежом в течение последнего десятилетия крупномасштабных агент-ориентированных моделей (мультиагентных систем). Рассмотрены основные аспекты, связанные с технической реализацией – процессом адаптации и запуска моделей на суперкомпьютерах (параллельных компьютерах): выбором методов распараллеливания моделей, оптимального специализированного программного обеспечения, программно-аппаратных средств для обеспечения высокой производительности параллельных вычислений. Показано многообразие научно-исследовательских задач, решаемых с помощью метода агент-ориентированного моделирования, являющегося современным инструментом анализа комплексных социальных, экономических, технологических и научных систем. Выявлены конструктивные особенности крупномасштабных моделей, реализация которых планируется их авторами с привлечением суперкомпьютерных технологий.

The article provides an overview of large-scale agent-based models (multi-agent systems) developed over the last decade, analyzing the main aspects, related to the technical implementation - the process of adaptation and running models on supercomputers (or parallel clusters). The variety of scientific-research tasks solved with the help of agent simulation is shown, as well as the design features of large-scale models are listed, and their realization is planned by their authors with the use of supercomputer technologies. The article has been prepared with the support of the Russian Science Foundation (Grant №14-18-01968).

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The authors declare that there are no conflicts of interest present.