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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... [see also Stallman and Sussman (1977)] for analyzing the performance of electronic circuits; and Genesereth (1978, 1979), for helping casual users of the MACSYMA mathematical formula manipulation system [Martin and Fateman (1971)].
An important part of the DENDRAL system involves the generation of candidate structures, given the chemical formula of the compound. A full explanation of how these candidate structures are generated is beyond the scope of our present ...
Any database that contains no unstructured formulas satisfies the termination condition. Briefly, we can illustrate how the ... Let us suppose that we are given the chemical formula C; H12. Our production system proposes some candidate ...
In the partial structures above, the formulas within vertical bars ( ) are unstructured. ... For example, the rules propose the following structure for the formula –C2H5|: | || "-i-gH H A partial AND/OR tree for our C. His problem is ...
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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