Introduction to 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. Front Matter....Pages i-x Front Matter....Pages 1-1 History of Artificial Intelligence....Pages 3-13 Symbolic Artificial Intelligence....Pages 15-22 Computational Intelligence....Pages 23-27 Front Matter....Pages 29-29 Search Methods....Pages 31-51 Evolutionary Computing....Pages 53-66 Logic-Based Reasoning....Pages 67-89 Structural Models of Knowledge Representation....Pages 91-101 Syntactic Pattern Analysis....Pages 103-124 Rule-Based Systems....Pages 125-139 Pattern Recognition and Cluster Analysis....Pages 141-156 Neural Networks....Pages 157-174 Reasoning with Imperfect Knowledge....Pages 175-188 Defining Vague Notions in Knowledge-Based Systems....Pages 189-201 Cognitive Architectures....Pages 203-210 Front Matter....Pages 211-211 Theories of Intelligence in Philosophy and Psychology....Pages 213-222 Application Areas of AI Systems....Pages 223-234 Prospects of Artificial Intelligence....Pages 235-245 Back Matter....Pages 247-321