Principles of Artificial IntelligenceA 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. |
From inside the book
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... chapter 3. We next discuss how decomposable production systems can be used on some example problems. 1.2.2.1. Chemical Structure Generation. An important problem in organic chemistry involves determining the structure of a complex ...
... chapters, is with control—especially graph-searching control regimes. Then we move on to consider the uses of the predicate calculus in Artificial Intelligence. 1.4. BIBLIOGRAPHICAL AND HISTORICAL REMARKS 1.4.1. PRODUCTION SYSTEMS The ...
... chapter 3. The problem of finding good representations for problems has been treated by only a few researchers. Amarel (1968) has written a classic paper on the subject; it takes the reader through a series of progressively better ...
... chapters. 1.4.3, EXAMPLE PROBLEMS Problem-solving programs have sharpened their techniques on a variety of puzzles and games. Some good general books of puzzles are those of Gardner (1959, 1961), who edits a puzzle column in Scientific ...
... a backtracking point, are there any differences between procedure SPLIT under backtracking and procedure PRODUCTION under backtracking? CHAPTER 2 SEARCH STRATEGIES FOR AI PRODUCTION SYSTEMS In this 52 PRODUCTION SYSTEMS AND AI.
Contents
1 | |
17 | |
53 | |
CHAPTER 3 SEARCH STRATEGIES FOR DECOMPOSABLE PRODUCTION SYSTEMS | 99 |
CHAPTER 4 THE PREDICATE CALCULUS IN AI | 131 |
CHAPTER 5 RESOLUTION REFUTATION SYSTEMS | 161 |
CHAPTER 6 RULEBASED DEDUCTION SYSTEMS | 193 |
CHAPTER 7 BASIC PLANGENERATING SYSTEMS | 275 |
CHAPTER 8 ADVANCED PLANGENERATING SYSTEMS | 321 |
CHAPTER 9 STRUCTURED OBJECT REPRESENTATIONS | 361 |
PROSPECTUS | 417 |
BIBLIOGRAPHY | 429 |
AUTHOR INDEX | 467 |
SUBJECT INDEX | 471 |