Principles of Artificial Intelligence
Morgan Kaufmann, Jun 28, 2014 - Computers - 476 pages
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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A computer system capable of understanding a message in natural language would seem, then, to require (no less than would ... Example items in such a database might be representations for such facts as “Joe Smith works in the Purchasing ...
Although there is no formal difference between a production system that works on a problem in a forward direction and one that works in a backward direction, it is often convenient to make this distinction explicit.
A full explanation of how these candidate structures are generated is beyond the scope of our present discussion, but we can give a brief description of how the process works for a simple hydrocarbon. The system for generating candidate ...
An estimate that works quite well for the 8-puzzle is h (n) = P(n) + 3S(n). The quantity S(n) is a sequence score obtained by checking around the noncentral squares in turn, allotting 2 for every tile not followed by its proper ...
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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