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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Instructors may find it useful to use selected exercises as a basis for class discussion. Pertinent references are briefly discussed at the end of every chapter. These citations should provide the interested student with adequate entry ...
We concentrate on those that find application in several different problem areas. In order to emphasize their generality, we explain these principles abstractly rather than discuss them in the ...
Even with this more limited outlook, our discussion of AI ideas might well be of interest to cognitive psychologists and others attempting to understand natural intelligence. As we have already mentioned, AI methods and techniques have ...
Many of these problems can be attacked by the methods discussed in this book. A classical example is the traveling salesman's problem, where the problem is to find a minimum distance tour, starting at one of several cities, ...
We discuss some of the fundamental ideas underlying frame-structured representations and inference processes later in the book. 0.2. OVERVIEW The book is divided into nine chapters and a prospectus. In chapter 1, we introduce a ...
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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