SIMULATING HUMAN DECISION MAKING: A COGNITIVE MODEL FOR PREDICTIVE ANALYTICS

Authors

  • CHRISTIANGE PALMIANO Author

Keywords:

cognitive modeling, human decision-making, predictive analytics, behavioral psychology, neural networks, probabilistic reasoning

Abstract

Human decision-making is a complex process influenced by cognitive, emotional, and contextual factors. This paper presents a cognitive model designed to simulate human decision-making within predictive analytics frameworks. The model integrates elements from behavioral psychology, neural networks, and probabilistic reasoning to capture the intricacies of human choices. Applications of this model are demonstrated in domains such as financial forecasting, healthcare decision support, and user behavior prediction. The study highlights the benefits of incorporating human-like reasoning into predictive models, improving their interpretability and relevance in real-world scenarios. Challenges related to model complexity, computational requirements, and ethical considerations are also explored, offering a roadmap for future research.

 

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Published

2024-12-28

How to Cite

SIMULATING HUMAN DECISION MAKING: A COGNITIVE MODEL FOR PREDICTIVE ANALYTICS. (2024). Cognify : Journal of Artificial Intelligence and Cognitive Science, 1(4), 38-47. https://researchvision.us/index.php/cognify/article/view/151

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