Method for constructing a cognitive map of processes in a dynamic system using cooperation of large language models
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In the context of growing demands for rapid decision-making and in-depth analysis of complex dynamic
systems – particularly when available data are limited and the involvement of experienced experts is either impractical
or prohibitively expensive – the development of new methods for the construction of the model becomes especially
relevant. The use of large language models (LLMs) as expert systems offers significant reductions in resource expenditure
and accelerates the modelling of complex technical, environmental, and socio-economic systems. This study aimed to
investigate and demonstrate the potential and capabilities of LLMs as expert systems in constructing cognitive maps.
The article proposes and substantiates an architecture for the cooperation of LLM ensembles to formally generate
vertices-variables and weight coefficients in cognitive maps, thereby enabling the automation of the modelling process
without the involvement of human experts. A typical prompt for an LLM was decomposed into structural components:
context description (D), model role instruction (R), instruction (I), conditions (C), and response format (F). A method for
determining these components through expert-based analysis is proposed. A prompt system was developed to enable
structured data processing and the identification of interrelationships among system elements. The practical effectiveness
of the approach was demonstrated using a case study on forecasting water quality in the Sabarivske Reservoir near
Vinnytsia. For most physicochemical indicators, the modelling showed low error rates (2.09-4.6%), even with a minimal
amount of input data. The proposed method is promising for modelling and forecasting tasks in complex systems with
limited data availability, particularly in environmental, socio-economic, and engineering contexts, where the speed of
obtaining reliable results is critical for informed decision-making.
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Varer B., Mokin V. Method for constructing a cognitive map of processes in a dynamic system using cooperation of large language models // Information Technologies and Computer Engineering. 2025. № 1 (22). С. 69-78. DOI: https://doi.org/10.63341/vitce/1.2025.69.
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