Discrete and Continuous Models and Applied Computational ScienceDiscrete and Continuous Models and Applied Computational ScienceDiscrete and Continuous Models and Applied Computational Science2658-46702658-7149Peoples' Friendship University of Russia named after Patrice Lumumba (RUDN University)4525810.22363/2658-4670-2025-33-2-214-225MKTGEJLettersПисьмаResearch ArticleOn modelling multi-agent systems based on large language modelsО моделировании мультиагентных систем на основе больших языковых моделейhttps://orcid.org/0000-0003-3651-762916408533100O-8287-2017ShchetininEugeny Yu.ЩетининЕ. Ю.

Doctor of Physical and Mathematical Sciences, Lecturer of Artificial Intelligence Department

riviera-molto@mail.ruhttps://orcid.org/0000-0003-4466-8531VelievaTatyana R.ВелиеваТ. Р.

Candidate of Physical and Mathematical Sciences, Senior lecturer of Department of Probability Theory and Cyber Security

velieva-tr@rudn.ruhttps://orcid.org/0009-0004-4661-5059YurginaLyubov A.ЮргинаЛ. А.

Ph.D. of Pedagogical Sciences, Head of the Department of Mathematics and Information Technology of the Sochi branch

yurgina_la@pfur.ruhttps://orcid.org/0000-0003-1000-9650DemidovaAnastasia V.ДемидоваА. В.

Candidate of Physical and Mathematical Sciences, Assistant Professor of Department of Probability Theory and Cyber Security

demidova-av@rudn.ruFinancial University under the Government of the Russian FederationФинансовый университет при Правительстве Российской ФедерацииRUDN UniversityРоссийский университет дружбы народов15072025332VOL 33, NO2 (2025)ТОМ 33, №2 (2025)21422525072025Copyright ©; 2025, Shchetinin E.Y., Velieva T.R., Yurgina L.A., Demidova A.V.Copyright ©; 2025, Щетинин Е.Ю., Велиева Т.Р., Юргина Л.А., Демидова А.В.2025Shchetinin E.Y., Velieva T.R., Yurgina L.A., Demidova A.V.Щетинин Е.Ю., Велиева Т.Р., Юргина Л.А., Демидова А.В.https://creativecommons.org/licenses/by-nc/4.0https://journals.rudn.ru/miph/article/view/45258

The article studies the effectiveness of implementation of multi-agent systems based on large language models in various spheres of human activity, analyses their advantages, problems and challenges. The results of the research have shown that multi-agent systems based on large language models have significant potential and wide opportunities in modelling various environments and solving various tasks.

В статье изучается эффективность внедрения мультиагентных систем на основе больших языковых моделей в различных сферах человеческой деятельности, анализируются их преимущества, проблемы и задачи. Результаты исследования показали, что мультиагентные системы на основе больших языковых моделей обладают значительным потенциалом и широкими возможностями в моделировании различных сред и решении различных задач.

multi-agent systemslarge language modelssociety modelingискусственный интеллектфинансовые рискибольшие данныеMinsky, M. Society of mind (Simon and Schuster, 1988).Russell, S. J. Artificial intelligence a modern approach (Pearson Education, Inc., 2010).Ginsberg, M. L. Essentials of Artificial Intelligence (Morgan Kaufmann, 1993).Wooldridge, M. & Jennings, N. R. Intelligent agents: theory and practice. The Knowledge Engineering Review 10, 115-152. doi:10.1017/S0269888900008122 (1995).Linardatos, P., Papastefanopoulos, V. & Kotsiantis, S. Explainable AI: A Review of Machine Learning Interpretability Methods. Entropy 23, 18. doi:10.3390/e23010018 (2021).Han, S., Zhang, Q., Yao, Y., Jin, W., Xu, Z. & He, C. LLM Multi-Agent Systems: Challenges and Open Problems 2024.Wang, L. et al. A survey on large language model based autonomous agents 2023.Andreas, J. Language Models as Agent Models in Findings of the Association for Computational Linguistics: EMNLP 2022 (eds Goldberg, Y., Kozareva, Z. & Zhang, Y.) (Association for Computational Linguistics, Abu Dhabi, United Arab Emirates, Dec. 2022), 5769-5779. doi:10.18653/v1/2022.findings-emnlp.423.Brooks, R. A. The artificial life route to artificial intelligence in. Chap. Intelligence without reason (Routledge, 2018).Openai: Introducing chatgpt. Website 2022.Thirunavukarasu, A., Ting, D., Elangovan, K., Gutierrez, L., Tan, T. & Ting, D. Large language models in medicine. Nature Medicine 29, 1930-1940. doi:10.1038/s41591-023-02448-8 (2023).Chan, C.-M., Chen, W., Su, Y., Yu, J., Xue, W., Zhang, S., Fu, J. & Liu, Z. ChatEval: Towards Better LLM-based Evaluators through Multi-Agent Debate 2023.Cai, T., Wang, X., Ma, T., Chen, X. & Zhou, D. Large language models as tool makers 2023.Wu, T., Terry, M. & Cai, C. J. AI Chains: Transparent and Controllable Human-AI Interaction by Chaining Large Language Model Prompts in Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (Association for Computing Machinery, New York, NY, USA, 2022), 385. doi:10.1145/3491102.3517582.Mohtashami, A. & Jaggi, M. Landmark attention: Random-access infinite context length for transformers 2023.Bar, A., Gandelsman, Y., Darrell, T., Globerson, A. & Efros, A. Visual Prompting via Image Inpainting in Advances in Neural Information Processing Systems (eds Koyejo, S., Mohamed, S., Agarwal, A., Belgrave, D., Cho, K. & Oh, A.) 35 (Curran Associates, Inc., 2022), 25005-25017.Mustakim, M., Pratama, A. R., Ahmad, I., Arifianto, T., Sussolaikah, K. & Sepriano, S. Image classification of corn leaf diseases using CNN architecture ResNet-50 and data augmentation in 2024 International Conference on Decision Aid Sciences and Applications (DASA) (2024), 1-6.Shchetinin, E. Y. On Using Computer Linguistic Models in the Classification of Biomedical Images. Mathematical Models and Computer Simulations 2 (2024).Shchetinin, E. Y., Glushkova, A. G. & Demidova, A. V. Developing a computer system for student learning based on vision-language models. Discrete and Continuous Models and Applied Computational Science 32, 234-241 (2024).Wu, Q. et al. AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation 2023.