The Influence of Data Structures on AI Decision-Making Processes
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Abstract: This research examines the impact of different data structures on the efficacy, precision, and efficiency of AI systems' decision-making. These data structures include arrays, linked lists, trees, graphs, and hash tables. Artificial intelligence's (AI) decision-making process is highly dependent on the data structures utilized to arrange, retrieve, and modify information. Knowing how data architectures affect AI decision-making is crucial as AI develops and applications get more complicated.
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References
Russell, S. J., & Norvig, P. (2020). Artificial Intelligence: A Modern Approach (4th ed.). Pearson.
Mitchell, T. M. (1997). Machine Learning. McGraw-Hill.
Artificial Intelligence, Tata McGraw Hill, Elaine Rich and Kevin Knight Cormen, T. H., Leiserson, C. E., Rivest, R. L., & Stein, C. (2009). Introduction to Algorithms. MIT Press.
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