THE ROLE OF MATHEMATICAL MODELING IN ARTIFICIAL INTELLIGENCE SYSTEMS

Authors

  • Babamuratov Jamshid Irkinovich Asia International University

DOI:

https://doi.org/10.55640/

Keywords:

Artificial intelligence, mathematical modeling, machine learning, neural networks, optimization, probabilistic models.

Abstract

Mathematical modeling plays a fundamental role in the development and functioning of artificial intelligence (AI) systems. It provides a formal framework for representing real-world processes, learning mechanisms, and decision-making strategies. This paper explores the significance of mathematical models in artificial intelligence, focusing on their application in machine learning, neural networks, optimization algorithms, and probabilistic reasoning. The study highlights how mathematical formalization improves system accuracy, interpretability, and scalability. Furthermore, current challenges and future research directions in mathematical modeling for AI systems are discussed.

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References

1.Bishop, C. M. (2006). Pattern Recognition and Machine Learning. Springer.

2.Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep Learning. MIT Press.

3.Russell, S., & Norvig, P. (2021). Artificial Intelligence: A Modern Approach. Pearson.

4.Vapnik, V. N. (1998). Statistical Learning Theory. Wiley.

5.Murphy, K. P. (2012). Machine Learning: A Probabilistic Perspective. MIT Press.

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Published

2026-01-31

How to Cite

THE ROLE OF MATHEMATICAL MODELING IN ARTIFICIAL INTELLIGENCE SYSTEMS. (2026). Journal of Multidisciplinary Sciences and Innovations, 5(01), 2516-2520. https://doi.org/10.55640/

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