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Introduction to Artificial Intelligence [electronic resource] / by Mariusz Flasiński.

By: Flasiński, Mariusz [author.].
Contributor(s): SpringerLink (Online service).
Material type: materialTypeLabelBookPublisher: Cham : Springer International Publishing : Imprint: Springer, 2016Description: X, 321 p. 70 illus. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783319400228.Subject(s): Computer science | Data mining | Artificial intelligence | Computational intelligence | Computer Science | Artificial Intelligence (incl. Robotics) | Computational Intelligence | Data Mining and Knowledge DiscoveryAdditional physical formats: Printed edition:: No titleDDC classification: 006.3 Online resources: Click here to access online
Contents:
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. .
In: Springer eBooksSummary: 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.
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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. .

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.

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