Principles of Artificial Intelligence
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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Although certain topics treated in my previous book, Problemsolving Methods in Artificial Intelligence, are covered here as well, this book contains many additional topics such as rule-based systems, ...
The problem generalizes to one of finding a minimum cost path over the edges of a graph containing n nodes such that the path visits each of the n nodes precisely once. Many puzzles have this same general character.
The window schema might contain the knowledge that windows typically do not touch the floor. A special detector, applied to the scene, confirms this expectation, thus raising confidence in the window hypothesis.
Nilsson's (1974) survey describes the field in the early 1970s and contains many references. Michie's (1974) book contains several of his articles on AI. Raphael's (1975) book and Winston's (1977) book are easy-to-read and elementary ...
Proceedings of biannual conferences on Theoretical Issues in Natural Language Processing (TINLAP) contain several important ... The article edited by Waltz (1977) contains several descriptions of systems for querying databases using ...
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CHAPTER 3 SEARCH STRATEGIES FOR DECOMPOSABLE PRODUCTION SYSTEMS
CHAPTER 4 THE PREDICATE CALCULUS IN AI
CHAPTER 5 RESOLUTION REFUTATION SYSTEMS
CHAPTER 6 RULEBASED DEDUCTION SYSTEMS
CHAPTER 7 BASIC PLANGENERATING SYSTEMS
CHAPTER 8 ADVANCED PLANGENERATING SYSTEMS
CHAPTER 9 STRUCTURED OBJECT REPRESENTATIONS