Introduction to Artificial Intelligence

Häftad, Engelska, 2018

AvMariusz Flasiński

889 kr

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In the chapters in Part I of this textbook the author introduces the fundamental ideas of artificial intelligence and computational intelligence. In Part II he explains key AI methods such as search, evolutionary computing, logic-based reasoning, knowledge representation, rule-based systems, pattern recognition, neural networks, and cognitive architectures. Finally, in Part III, he expands the context to discuss theories of intelligence in philosophy and psychology, key applications of AI systems, and the likely future of artificial intelligence. A key feature of the author's approach is historical and biographical footnotes, stressing the multidisciplinary character of the field and its pioneers.The book is appropriate for advanced undergraduate and graduate courses in computer science, engineering, and other applied sciences, and the appendices offer short formal, mathematical models and notes to support the reader.

Produktinformation

Utgivningsdatum2018-06-07
Mått155 x 235 x 19 mm
Vikt505 g
FormatHäftad
SpråkEngelska
Antal sidor321
FörlagSpringer International Publishing AG
ISBN9783319820163
OriginaltitelWstęp do sztucznej inteligencji

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Artificiell intelligens inom Data och IT
Databaser inom Data och IT

History of Artificial Intelligence.- Symbolic Artificial Intelligence.- Computational Intelligence.- Search Methods.- Evolutionary Computing.- Logic-Based Reasoning.- Structural Models of Knowledge Representation.- Syntactic Pattern Analysis.- Rule-Based Systems.- Pattern Recognition and Cluster Analysis.- Neural Networks.- Reasoning with Imperfect Knowledge.- Defining Vague Notions in Knowledge-Based Systems.- Cognitive Architectures.- Theories of Intelligence in Philosophy and Psychology.- Application Areas of AI Systems.- Prospects of Artificial Intelligence.

“The book is very useful for computer science, engineering, and allied science students, particularly because of the extensive appendices giving formal mathematical models for AI methods. However, because AI is a multi-disciplinary area today, students and researchers from disciplines like psychology, philosophy, and linguistics who are interested in studying and researching AI further will also benefit from using this book for a first AI course … .” (C. S. Arora, Computing Reviews, January, 2017)

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