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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I look forward someday to revising this book—to correct its inevitable errors, and to add new results and points of view. Toward that end, I solicit ...
The task of automatically writing a program to achieve a stated result is closely related to the task of proving that a given program achieves a stated ...
... goals of a research project to develop a speech understanding system; the major results of this research are described in papers by Medress et al.
Wos and his co-workers have achieved excellent results with resolution-based systems [McCharen et al. (1976); Winker and Wos (1978); Winker (1979)].
... do: 3 begin 4 select some rule, R, in the set of rules that can be applied to DATA 5 DATA - result of applying R to DATA 6 end 1.1.3.
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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