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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To take a specific example, suppose the facts are the personnel records of a large corporation. Example items in such a database might be representations ...
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, ...
For example, perhaps a detector could be built that could test a scene to see if it belonged to the category “A hill with a tree on top ...
Such a condition implicitly defines some set of goal states. For example, in the 8-puzzle, we might want to achieve any tile configuration for which the ...
EXAMPLES OF CONTROL REGIMES 220.127.116.11. Irrevocable. ... Trial-and-error methods seem to be inherent in solving puzzles, for example.
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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