Using Agent-Based Modeling to Study the Adaptation and Evolution of Human Emotions and Cognition*

Duan Qin, Luo Siyang

Journal of Psychological Science ›› 2025, Vol. 48 ›› Issue (6) : 1314-1332.

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Journal of Psychological Science ›› 2025, Vol. 48 ›› Issue (6) : 1314-1332. DOI: 10.16719/j.cnki.1671-6981.20250603

Using Agent-Based Modeling to Study the Adaptation and Evolution of Human Emotions and Cognition*

  • Duan Qin1, Luo Siyang1
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Abstract

This review explores the use of agent-based modeling (ABM) within the framework of study human emotion and cognition in the context of its ability to simulate complex social interactions, adaptive changes, and evolutionary processes. By representing agents and their defined environments with probabilistic interactions, ABM allows the assessment of the effects of individual behavior at the micro level on the greater social phenomena at the macro level. The review looks into the applications of ABM in portraying some of the key components of emotions and cognition—empathy, cooperation, decision making, and emotional transmission—and analyzes the problems including scalability, empirical validation, and description of sensitive emotional states. The most important conclusion is that merging ABM with information neurobiological data and artificial intelligence (AI) techniques would allow for deepening the interactions within the system and enhancing its responsiveness to stimuli. This review highlights approaches that aim to exploit the ABM methodology more fully and integrates methods from biology, neuroscience, and engineering. This integration could contribute to our understanding of the human behavior evolution and adaptation within systems relevant to policymaking, healthcare, and education.

Key words

agent-based modeling / emotions evolution / cognition evolution / social interactions

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Duan Qin, Luo Siyang. Using Agent-Based Modeling to Study the Adaptation and Evolution of Human Emotions and Cognition*[J]. Journal of Psychological Science. 2025, 48(6): 1314-1332 https://doi.org/10.16719/j.cnki.1671-6981.20250603

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