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<p>A novel functional model of a dynamic cognitive system, designed to simulate agent behavior in complex socio-informational environments is considered. The proposed approach integrates cognitive, emotional, motivational, and social components within a unified hierarchical architecture supported by multimodal data collection. Special emphasis is placed on the use of state-of-the-art machine learning techniques to optimize action-selection policies, enhance prediction accuracy, and improve adaptability to exogenous disturbances. The simulation results demonstrate the model’s relevance for scenario analysis, identifying the dynamics of recovery after information shocks, and revealing the internal structure of group behavior. The results obtained provide a basis for the practical application of the model in strategic management, education, rehabilitation, and social analytics.</p>

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Agent Behavior Prediction Based on a Dynamic Cognitive Model

  • 期刊论文

  • 发表日期：

    2026年3月1日

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  • O. Palagin,
  • D. Symonov,
  • O. Symonova

摘要

A novel functional model of a dynamic cognitive system, designed to simulate agent behavior in complex socio-informational environments is considered. The proposed approach integrates cognitive, emotional, motivational, and social components within a unified hierarchical architecture supported by multimodal data collection. Special emphasis is placed on the use of state-of-the-art machine learning techniques to optimize action-selection policies, enhance prediction accuracy, and improve adaptability to exogenous disturbances. The simulation results demonstrate the model’s relevance for scenario analysis, identifying the dynamics of recovery after information shocks, and revealing the internal structure of group behavior. The results obtained provide a basis for the practical application of the model in strategic management, education, rehabilitation, and social analytics.