Titlebook: Artificial Intelligence; A Textbook Charu C. Aggarwal Textbook 2021 Springer Nature Switzerland AG 2021 Artificial Intelligence.Machine Lea

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Concurrency and Multiversioning,-and-error in simplifying the design of highly complex learning algorithms. We have already seen one form of this trial and error in the chapter on adversarial search (cf. Chapter .), where Monte Carlo trees are used to learn the best chess moves through trial and error.

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Reinforcement Learning,-and-error in simplifying the design of highly complex learning algorithms. We have already seen one form of this trial and error in the chapter on adversarial search (cf. Chapter .), where Monte Carlo trees are used to learn the best chess moves through trial and error.

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asoning and inductive learning.Provides more balanced covera.This textbook covers the broader field of artificial intelligence.   The chapters for this textbook span within three categories:.Deductive reasoning methods:. These methods start with pre-defined hypotheses and reason with them in order t

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Textbook 2021 and neuro-symbolic artificial intelligence..The primary audience for this textbook are professors and advanced-level students in computer science. It is also possible to use this textbook for the mathematics requirements for an undergraduate data science course. Professionals working in this relate

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https://doi.org/10.1007/978-3-030-72357-6Artificial Intelligence; Machine Learning; Deep Learning; Neural Networks; Data Mining; Search; Logic Prog

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