Conceptual model of a multi-agent innovative investment system using neurocognitive architectures

A.A. Aigumov, I.A. Pshenokova

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Abstract: The relevance of this study stems from the need to develop effective tools for managing innovative investment processes in a highly uncertain market environment. Traditional research approaches, such as econometric modeling or system dynamics, often encounter difficulties in describing the adaptive behavior of agents and unpredictable collective effects. Therefore, there is a need for tools that allow for more realistic simulation of the behavior of investment market participants in all its complexity.
Aim. The study is to develop and test a multi-agent model to evaluate the effectiveness of various innovative investment scenarios and identify optimal strategies for market participants.
Methods. This paper uses simulation and multi-agent modeling as the primary research methods.
Results. This article presents a multi-agent simulation model of an innovative investment system for analyzing interactions between investment market participants. Simulation experiments demonstrate that the developed model is able to replicate the dynamics of innovation system development, evaluate the effectiveness of various investment strategies, predict market participant behavior, and determine optimal parameters for interactions between agents.
Conclusions. Future studies propose expanding the model to include a more detailed classification of investors and projects, integration with real data, and additional learning and collective investment mechanisms.The developed model can serve as a basis for creating practical decision-making tools for innovative investment and contribute to improving the efficiency of investment activities.

Keywords: simulation modeling, cognitive modeling, multi-agent model, innovative investing

For citation. Aigumov A.A., Pshenokova I.A. Conceptual model of a multi-agent innovative investment system using neurocognitive architectures. News of the Kabardino-Balkarian Scientific Center of RAS. 2025. Vol. 27. No. 5. Pp. 13–25. DOI: 10.35330/1991-6639-2025-27-5-13-25

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Information about the authors

Arslan A. Aigumov, Postgraduate Student of the Department of Мulti-Аgent Intellectual Robotics Systems of the Scientific and Educational Center, Kabardino-Balkarian Scientific Center of the Russian Academy of Sciences;
2 Balkarov street, Nalchik, 360010, Russia;
arrrslan@mail.ru
Inna A. Pshenokova, Candidate of Physical and Mathematical Sciences, Head of the Research Center “Intellectual Integrated Information and Management Systems”, Kabardino-Balkarian Scientific Center of the Russian Academy of Sciences;
2 Balkarov street, Nalchik, 360010, Russia;
Associate Professor of the Department of Computer Technology and Information Security, KabardinoBalkarian State University named after Kh.M. Berbekov;
173 Chernyshevsky street, Nalchik, 360004, Russia;
pshenokova_inna@mail.ru, ORCID: https://orcid.org/0000-0003-3394-7682, SPIN-code: 3535-2963