A classic introduction to artificial intelligence intended to bridge the gap between theory and practice, Principles of Artificial Intelligence describes fundamental AI ideas that underlie applications such as natural language processing, automatic programming, robotics, machine vision, automatic theorem proving, and intelligent data retrieval. Rather than focusing on the subject matter of the applications, the book is organized around general computational concepts involving the kinds of data structures used, the types of operations performed on the data structures, and the properties of the control strategies used.
Principles of Artificial Intelligenceevolved from the author's courses and seminars at Stanford University and University of Massachusetts, Amherst, and is suitable for text use in a senior or graduate AI course, or for individual study.
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Elsevier Science & Technology
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978-0-934613-10-1 (9780934613101)
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Schweitzer Klassifikation
Nils J. Nilsson's long and rich research career has contributed much to AI. He has written many books, including the classic Principles of Artificial Intelligence. Dr. Nilsson is Kumagai Professor of Engineering, Emeritus, at Stanford University. He has served on the editorial boards of Artificial Intelligence and Machine Learning and as an Area Editor for the Journal of the Association for Computing Machinery. Former Chairman of the Department of Computer Science at Stanford, and former Director of the SRI Artificial Intelligence Center, he is also a past president and Fellow of the American Association for Artificial Intelligence.
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Stanford University
CHAPTER 1: PRODUCTION SYSTEMS AND AI
CHAPTER 2: SEARCH STRATEGIES FOR AI PRODUCTION SYSTEMS
CHAPTER 3: SEARCH STRATEGIES FOR DECOMPOSABLE PRODUCTION SYSTEMS
CHAPTER 4: THE PREDICATE CALCULUS IN AI
CHAPTER 5: RESOLUTION REFUTATION SYSTEMS
CHAPTER 6: Rule-Based Deduction Systems
CHAPTER 7: BASIC PLAN-GENERATING SYSTEMS
CHAPTER 8: ADVANCED PLAN-GENERATING SYTEMS
CHAPTER 9: STRUCTURED OBJECT REPRESENTATIONS
Prospectus