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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In chapters 7 and 8, we present methods for synthesizing sequences of actions that achieve prescribed goals. These methods are illustrated by considering simple problems in robot planning and automatic programming. Chapter 7 introduces ...
(1971) and Raphael (1976, chapter 8); for the Stanford University work by McCarthy et al. (1969); and for the Edinburgh work by Ambler, et al. (1975). Practical applications of robotics in industrial automation are becoming commonplace.
... see the book by Weissman (1967). Friedman (1974) is an entertaining programmed instruction manual. For a more technical treatment, see the book by Allen (1978). CHAPTER 1 PRODUCTION SYSTEMS AND AI Most AI systems display 16 PROLOGUE.
CHAPTER 1 PRODUCTION SYSTEMS AND AI Most AI systems display a more or less rigid separation between the standard computational components of data, operations, and control. That is, if these systems are described at an appropriate level, ...
... keeping track of the effects of several sequences of rules. We will be discussing these structures in much more detail in chapters 2 and 3, giving only a short example here of their use. 8 2 l (6) 8 2 1 (7) 8 2 25 PRODUCTION SYSTEMS.
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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 RULEBASED DEDUCTION SYSTEMS
CHAPTER 7 BASIC PLANGENERATING SYSTEMS
CHAPTER 8 ADVANCED PLANGENERATING SYSTEMS
CHAPTER 9 STRUCTURED OBJECT REPRESENTATIONS