THEORETICAL FOUNDATIONS OF ARTIFICIAL INTELLIGENCE

Nikolay Nikolov ()
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Nikolay Nikolov: University of Economics - Varna / Department of Informatics, Varna, Bulgaria

Conferences of the department Informatics, 2024, issue 1, 182-186

Abstract: This paper explores the theoretical principles underlying artificial intelligence (AI) algorithms. The focus is on the mathematical and algorithmic models that enable machines to acquire, represent, and utilize knowledge. Concepts from linear algebra, probability theory, and statistics, which are critical for understanding machine learning and deep neural networks, are examined. Various learning methods, including supervised, unsupervised, and reinforcement learning, are analyzed. The paper also discusses the role of algorithmic complexity and computational efficiency in the development of scalable AI systems. In conclusion, future directions and research questions related to the theoretical aspects of artificial intelligence are presented.

Keywords: artificial intelligence; algorithms; machine learning; neural networks (search for similar items in EconPapers)
JEL-codes: C8 (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:vrn:katinf:y:2024:i:1:p:182-186

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